EPSRC-NIHR HTC Partnership Award 'Plus': Medical Image Analysis Network (MedIAN)
Lead Research Organisation:
University of Oxford
Department Name: Engineering Science
Abstract
The EPSRC-NIHR Healthcare Technology Co-operatives Partnership Network in Medical Image Analysis seeks to bring leading UK researchers in medical image analysis together to identify new opportunities for medical image analysis methodology research within the clinical areas of high morbidity/unmet need of the NIHR Cardiovascular HTC and HTC in Colorectal Therapies.
The HTCs are working with patient groups and clinicians on identifying unmet clinical needs in these areas. An aim of the Medical Image Analysis Network (MedIAN) is to bring together imaging scientists with different skills sets and experiences to consider how technological advances in how images are acquired and images (and associated information) are analysed can be applied to solve some of these problems.
The primary purpose of the Network is to encourage new collaborations to be set up between academic healthcare technologists, clinicians and industry partners to develop and evaluate new solutions. Network members are jointly tasked to work on some of the hardest medical image analysis problems there are today. The hope is that the resulting research will lead to new image-based biomarkers and quantification methods which will allow earlier detection of disease, and better stratification of disease so that the most appropriate therapy can be selected for a patient, and new image-based quantitative tools will lead to increases success of interventions and therapies and improve the
overall well-being of patients with these conditions.
How is MedIAN aiming achieve this goal? MedIAN is encouraging the development of new collaborations through scientific meetings with other networks/organisations, Clinical Readiness events which allow clinicians to evaluate current methods, and Challenge competitions which allow the international medical image analysis community to benchmark method on given clinical problems.
This new award will augment the existing one by enabling a number of new activities to be run: People and Knowledge Exchanges between UK research groups for early career researchers, Medical Image Analysis hackathons, Scoping Workshops to help work-up grant proposals and the facilitation of two national meetings for early career researchers (ECRs) working in medical image analysis which will be run by ECRs for ECRs. The new award will also enable a new internet resource to be set up which aims to be a focal information portal for UK medical image analysis researchers and those who wish to work with them.
The HTCs are working with patient groups and clinicians on identifying unmet clinical needs in these areas. An aim of the Medical Image Analysis Network (MedIAN) is to bring together imaging scientists with different skills sets and experiences to consider how technological advances in how images are acquired and images (and associated information) are analysed can be applied to solve some of these problems.
The primary purpose of the Network is to encourage new collaborations to be set up between academic healthcare technologists, clinicians and industry partners to develop and evaluate new solutions. Network members are jointly tasked to work on some of the hardest medical image analysis problems there are today. The hope is that the resulting research will lead to new image-based biomarkers and quantification methods which will allow earlier detection of disease, and better stratification of disease so that the most appropriate therapy can be selected for a patient, and new image-based quantitative tools will lead to increases success of interventions and therapies and improve the
overall well-being of patients with these conditions.
How is MedIAN aiming achieve this goal? MedIAN is encouraging the development of new collaborations through scientific meetings with other networks/organisations, Clinical Readiness events which allow clinicians to evaluate current methods, and Challenge competitions which allow the international medical image analysis community to benchmark method on given clinical problems.
This new award will augment the existing one by enabling a number of new activities to be run: People and Knowledge Exchanges between UK research groups for early career researchers, Medical Image Analysis hackathons, Scoping Workshops to help work-up grant proposals and the facilitation of two national meetings for early career researchers (ECRs) working in medical image analysis which will be run by ECRs for ECRs. The new award will also enable a new internet resource to be set up which aims to be a focal information portal for UK medical image analysis researchers and those who wish to work with them.
Planned Impact
The main non-academic beneficiaries of MedIAN activities are patients, clinicians, establishments where treatment happens, and companies that make healthcare products.
Clinical Impact:
The HTC partners will take the lead on this. The HTCs will use their knowledge gleaned from interactions with NHS Patient & Public Involvement groups, and clinicians linked to their HTC to pose new challenges to MedIAN members that may lead to technical solutions to some of the most challenging problems in diagnosis and treatment of patients with high morbidity conditions. Clinical impact at network award end will be measured in terms of the degree of active engagement of clinicians in the network and as partners on feasibility studies and grant submissions.
Commercial Impact:
The technology area of interest of this Network is likely to be of great interest to industry (imaging companies, medtech companies who use imaging for guidance, and medical diagnostic companies). The timeline from concept to product is typically of the order of 5-7 years in this area, so it unlikely that there will commercial success stories to report by award end. Commercial impact at network award end may be measured in terms of the degree of active engagement and support of industry in the network and as partners on
grant submissions. Intellectual Property may also be generated in feasibility projects and protection will be managed following the standard practices of the institutions involved.
Societal Impact:
The Network aims to make its own unique contribution to improving healthcare products and services, and through this, improve the quality of life of patients with high morbidity conditions. Direct benefits of network outputs are likely to be realised in the medium term. However, the network aims to contribute to societal needs for better solutions for rapid and early detection of conditions, and personalised surgery to improve patient outcome, as well as to reduce the cost of healthcare by developing healthcare technology solutions that will encourage clinical adoption of lower-cost imaging technology.
Clinical Impact:
The HTC partners will take the lead on this. The HTCs will use their knowledge gleaned from interactions with NHS Patient & Public Involvement groups, and clinicians linked to their HTC to pose new challenges to MedIAN members that may lead to technical solutions to some of the most challenging problems in diagnosis and treatment of patients with high morbidity conditions. Clinical impact at network award end will be measured in terms of the degree of active engagement of clinicians in the network and as partners on feasibility studies and grant submissions.
Commercial Impact:
The technology area of interest of this Network is likely to be of great interest to industry (imaging companies, medtech companies who use imaging for guidance, and medical diagnostic companies). The timeline from concept to product is typically of the order of 5-7 years in this area, so it unlikely that there will commercial success stories to report by award end. Commercial impact at network award end may be measured in terms of the degree of active engagement and support of industry in the network and as partners on
grant submissions. Intellectual Property may also be generated in feasibility projects and protection will be managed following the standard practices of the institutions involved.
Societal Impact:
The Network aims to make its own unique contribution to improving healthcare products and services, and through this, improve the quality of life of patients with high morbidity conditions. Direct benefits of network outputs are likely to be realised in the medium term. However, the network aims to contribute to societal needs for better solutions for rapid and early detection of conditions, and personalised surgery to improve patient outcome, as well as to reduce the cost of healthcare by developing healthcare technology solutions that will encourage clinical adoption of lower-cost imaging technology.
Organisations
- University of Oxford (Lead Research Organisation)
- UK Biobank (Collaboration)
- Oxford Academic Health Science Network (Collaboration)
- INTELLIGENT ULTRASOUND LTD (Collaboration)
- Medical Image Understanding and Analysis (Collaboration)
- Engineering and Physical Sciences Research Council (EPSRC) (Collaboration)
- Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) (Collaboration)
- Addenbrooke's Hospital (Collaboration)
- National Institute for Health Research (Collaboration)
Publications
Fehri H
(2019)
Bayesian Polytrees With Learned Deep Features for Multi-Class Cell Segmentation.
in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Albà X
(2018)
Automatic initialization and quality control of large-scale cardiac MRI segmentations.
in Medical image analysis
Oksuz I
(2019)
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.
in Medical image analysis
Oda H
(2017)
Automated mediastinal lymph node detection from CT volumes based on intensity targeted radial structure tensor analysis.
in Journal of medical imaging (Bellingham, Wash.)
Ali S
(2020)
An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy.
in Scientific reports
Hu Y
(2020)
AIDAN: An Attention-Guided Dual-Path Network for Pediatric Echocardiography Segmentation
in IEEE Access
Schnabel JA
(2016)
Advances and challenges in deformable image registration: From image fusion to complex motion modelling.
in Medical image analysis
Deng S
(2021)
A Virtual Reality System for Improved Image-Based Planning of Complex Cardiac Procedures.
in Journal of imaging
Clough JR
(2022)
A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology.
in IEEE transactions on pattern analysis and machine intelligence
Fuin N
(2020)
A multi-scale variational neural network for accelerating motion-compensated whole-heart 3D coronary MR angiography.
in Magnetic resonance imaging
Swierczynski P
(2018)
A level-set approach to joint image segmentation and registration with application to CT lung imaging.
in Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Toussaint N
(2021)
A landmark-free morphometrics pipeline for high-resolution phenotyping: application to a mouse model of Down syndrome.
in Development (Cambridge, England)
Roque T
(2018)
A DCE-MRI Driven 3-D Reaction-Diffusion Model of Solid Tumor Growth.
in IEEE transactions on medical imaging
| Description | The network's objectives were to promote greater national engagement of researchers working in this inter-disciplinary field by: - Running or co-organising one-day scientific events - Supporting ECRs by providing funds associated with organising international workshops - Organising an annual 2-day sand pit dedicated event for ECRs. - Running a website/digital resource for researchers working in the field. - Funding an ECR Knowledge Exchange Programme enabling ECRs to spend a period of time in another institution. - In 2018 we sponsored attendance of UK ECRs at an international conference and we have annually sponsored the national meeting in our field (MIUA). - In 2019 we funded two by-invitation workshops from academics from across the UK to discuss the health of medical image analysis in the UK and sustainability of the network post award. |
| Exploitation Route | As a network award, the outcome was to encourage greater engagement between parties at that time, to generate new collaborations leading to funded research collaborations and also to help the career development of researchers. There has been no funding opportunity to continue the network. As often happens, networks come and go and reconnection appear in different ways. The pandemic has also not helped as face-to-face meetings and engagement has stopped. Though it can't be readily measured, the connection between the large medical image analysis groups in the UK remains very strong with join publications, and running of international and national meetings, workshops and networks. Most of the groups are independently connecting with other sub-disciplines (academic and industry partners) to generate new research directions, for instance in the application of trusted research environments/federated analysis to medical imaging and in different areas of clinical medicine. An example is the UK Network on In Silico Trials (Frangi lead: insilicouk.slack.com). UK researchers (Noble (Oxford) and Hu (UCL)) have also set up an international workshop on ultrasound image analysis (ASMUS, now at the third edition) and a MICCAI Special Interest Group on Ultrasound having first collaborated via a network funded Knowledge Exchange visit. |
| Sectors | Digital/Communication/Information Technologies (including Software),Financial Services, and Management Consultancy,Healthcare |
| Description | This was a Network grant. It's primary objective was therefore to encourage networking between organisations/partners and to support the professional growth of ECRs. Thus there is no direct socio-economic benefit from the grant. The indirect benefit has been new networking relationships which were strengthened by engagement with grant events and activities. Refer to the grants associated with this entry. Covid-19 affected the followon as all face-to-face interactions stopped and the general desire and ability to network was unfortunately hampered in the last two years of the award (2021,2022). |
| First Year Of Impact | 2021 |
| Sector | Healthcare |
| Impact Types | Societal,Economic |
| Description | MICCAI Code of Conduct |
| Geographic Reach | Multiple continents/international |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Impact | Prof AF Frangi, as General Chair of MICCAI 2018 in Granada, Spain, for the first time developed and implemented a Code of Conduct that required to be agreed by any attendee to the meeting. Unfortunately, we had a serious case as part of the meeting in 2018, which was handled and led to a public annoucement http://www.miccai.org/news/2019/09/26/public-statement-from-the-miccai-board-violation-of-the-code-of-conduct-at-miccai-2018. We believe that members of MedIAN have contributed to deal with a better equality and diversity in our main conference. As a professional scientific society, the Medical Image Computing and Computer Assisted Intervention Society (MICCAI) is committed to providing an atmosphere that encourages the free expression and exchange of ideas. Consistent with this commitment, it was the purpose of this Code of Conduct to detail how MICCAI envisions that participants in MICCAI activities enjoy a safe, welcoming, and inclusive environment, free from threatening conduct, harassment, bullying, and intimidation. We believe the UK community has contributed to make this possible in a very instrumental way. |
| URL | http://www.miccai.org/about-miccai/code-of-conduct/ |
| Description | Strategic research agenda for biomedical imaging. |
| Geographic Reach | Europe |
| Policy Influence Type | Participation in a guidance/advisory committee |
| Impact | This Strategic Research Agenda identifies current challenges and needs in healthcare, illustrates how biomedical imaging and derived data can help to address these, and aims to stimulate dedicated research funding efforts.Medicine is currently moving towards a more tailored, patient-centric approach by providing personalised solutions for the individual patient. Innovation in biomedical imaging plays a key role in this process as it addresses the current needs for individualised prevention, treatment, therapy response monitoring, and image-guided surgery.The use of non-invasive biomarkers facilitates better therapy prediction and monitoring, leading to improved patient outcomes. Innovative diagnostic imaging technologies provide information about disease characteristics which, coupled with biological, genetic and -omics data, will contribute to an individualised diagnosis and therapy approach.In the emerging field of theranostics, imaging tools together with therapeutic agents enable the selection of best treatments and allow tailored therapeutic interventions.For prenatal monitoring, the use of innovative imaging technologies can ensure an early detection of malfunctions or disease.The application of biomedical imaging for diagnosis and management of lifestyle-induced diseases will help to avoid disease development through lifestyle changes.Artificial intelligence and machine learning in imaging will facilitate the improvement of image interpretation and lead to better disease prediction and therapy planning.As biomedical imaging technologies and analysis of existing imaging data provide solutions to current challenges and needs in healthcare, appropriate funding for dedicated research is needed to implement the innovative approaches for the wellbeing of citizens and patients. |
| URL | https://www.ncbi.nlm.nih.gov/pubmed/30693378 |
| Description | Breakthroughs in Quantitative Magnetic resonance ImagiNg for improved DEtection of brain Diseases |
| Amount | € 3,861,067 (EUR) |
| Funding ID | 764513 |
| Organisation | European Commission H2020 |
| Sector | Public |
| Country | Belgium |
| Start | 01/2018 |
| End | 12/2021 |
| Description | CardioX: integrated and quantitative cardiac imaging reports for Precision Cardiology within LTHT |
| Amount | £79,830 (GBP) |
| Funding ID | POC 000041 |
| Organisation | Grow MedTech |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 10/2019 |
| End | 09/2020 |
| Description | EPSRC Centre for Doctoral Training in Smart Medical Imaging at King's College London and Imperial College London |
| Amount | £6,022,394 (GBP) |
| Funding ID | EP/S022104/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2019 |
| End | 03/2028 |
| Description | EPSRC Healthcare Impact Partnerships |
| Amount | £950,000 (GBP) |
| Funding ID | EP/P023509/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2017 |
| End | 09/2020 |
| Description | EPSRC Research Grant |
| Amount | £707,983 (GBP) |
| Funding ID | EP/R005982/1, EP/R005516/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2018 |
| End | 01/2021 |
| Description | ERC Starting Grant |
| Amount | € 1,500,000 (EUR) |
| Organisation | European Commission H2020 |
| Sector | Public |
| Country | Belgium |
| Start | 02/2018 |
| End | 01/2023 |
| Description | Educational Stipend for Students |
| Amount | $450 (USD) |
| Organisation | International Society for Magnetic Resonance in Medicine (ISMRM) |
| Sector | Charity/Non Profit |
| Country | United States |
| Start | 04/2017 |
| End | 04/2017 |
| Description | Healthcare Impact Partnership |
| Amount | £932,050 (GBP) |
| Funding ID | EP/P023509/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2017 |
| End | 09/2020 |
| Description | INSILEX: Precision Computational Medicine for \textit{in silico} Trials of Medical Devices |
| Amount | £2,760,000 (GBP) |
| Funding ID | CiET1819/19 |
| Organisation | Royal Academy of Engineering |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 05/2018 |
| End | 04/2029 |
| Description | Improving the early detection of lung cancer by combining exosomal analysis of hypoxia with standard of care imaging |
| Amount | £531,701 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 04/2019 |
| End | 03/2023 |
| Description | Learned Society Fund 16/17 - Funding for conference/workshop attendance |
| Amount | £500 (GBP) |
| Organisation | University of Sheffield |
| Department | Learned Societies Fund (University of Sheffield) |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 04/2017 |
| End | 04/2017 |
| Description | London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare |
| Amount | £9,985,272 (GBP) |
| Funding ID | 104691 |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2019 |
| End | 01/2022 |
| Description | MRC Industrial CASE studentship |
| Amount | £104,565 (GBP) |
| Funding ID | MR/N018028/1 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2017 |
| End | 03/2021 |
| Description | Medtronic / Royal Academy of Engineering Research Chair in Machine Learning for Computer-assisted Neurosurgery |
| Amount | £216,698 (GBP) |
| Funding ID | RCSRF1819\7\34 |
| Organisation | Royal Academy of Engineering |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 10/2018 |
| End | 09/2023 |
| Description | OCEAN: One-stop-shop microstructure-sensitive perfusion/diffusion MRI: Application to vascular cognitive impairment |
| Amount | £58,452 (GBP) |
| Funding ID | EP/M006328/2 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 11/2018 |
| End | 06/2019 |
| Description | Royal Society International Exchange |
| Amount | £12,000 (GBP) |
| Organisation | The Royal Society |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 03/2015 |
| End | 02/2016 |
| Description | Automatic quality assessment pipeline for cardiac MR images acquired at the UK Biobank |
| Organisation | UK Biobank |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | We deployed a cloud-based solution to fully automate the full coverage of the heart on images acquired at the UK Biobank. Ensuring full coverage of the Left Ventricle (LV) is a basic criterion of CMR image quality. Complete LV coverage, from base to apex, precedes accurate cardiac volume and functional assessment. Incomplete coverage of the LV is identified through visual inspection, which is time-consuming and usually done retrospectively in large imaging cohorts. Our pipeline implemented an automatic method to analyse the data and check the coverage of LV from CMR images by using discriminative 3D (D3D) convolutional neural networks (CNNs). To identify missing basal and apical slices in a CMR volume, a two-stage approach is implemented. First, the D3D CNN extracts high-level features from the CMR stacks; subsequently, these image attributes are used to detect missing basal and apical slices. The well-trained attribute classifiers are performed on the candidates to corresponding quality categories. The model has been validated by training with UKBB pilot datasets and applying them to CMR datasets from Data Science Bowl Cardiac Challenge. The proposed model shows a high consistency with human perception and becomes superior compared to other state-of-the-art methods [1]. [1] Le Zhang*, Ali Gooya, Bo Dong, Marco Pereanez, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Alejandro F. Frangi Automatic Assessment of Full LV Coverage in Cardiac Cine MRI Using Learned Intensity Attributes with Discriminative 3D CNNs |
| Collaborator Contribution | Each day, DICOM images of patients are acquired at the UK-Biobank centres and stored in a Central NAS Backup. Our platform, MULTI-X UKBB processes these images using the Full Coverage "module". A Quality Control (QC) dashboard has been implemented to display the output of the analysis, providing immediate information of the images acquired. The same dashboard could be updated in the future, in order to add other QC components. The analysis pipeline can be divided into three steps: 1. Each night, all heart images acquired at the centre, previously anonymised, and organised by subject ID, are uploaded in bulk to a secured cloud storage location. 2. An automated process triggers the Full Coverage analysis, using cloud on-demand resources. Results are saved in a database for further analysis. 3. The QC dashboard is updated with the cases processed. Any issues are highlighted with a red flag. The dashboard includes visual elements and reporting tools for the analysis. |
| Impact | A Quality Control (QC) dashboard has been implemented to display the output of the analysis, providing immediate information of the images acquired. The same dashboard could be updated in the future, in order to add other QC components. |
| Start Year | 2018 |
| Description | Clinical collaboration |
| Organisation | Addenbrooke's Hospital |
| Department | Kidney Transplant Team |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | We have been developing software for brain lesion quantification used in clinical research by our collaborator. |
| Collaborator Contribution | Our collaborator has provided research and clinical data for method development and evalaution. |
| Impact | See publication output. |
| Start Year | 2016 |
| Description | EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Department | Centre For Mathematical And Statistical Analysis Of Multimodal Clinical Imaging |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Attend and participate in the EPSRC Centre's annual meeting. |
| Collaborator Contribution | Sharing of knowledge between networks. |
| Impact | Sharing of knowledge between network members. |
| Start Year | 2017 |
| Description | Intelligent Ultrasound Ltd |
| Organisation | Intelligent Ultrasound Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Partner on EPSRC/Innovate UK SMI Project. |
| Collaborator Contribution | Licence agreement to use IDF software for research purposes. Licence to use AQABUS software for research purposes. IU is an medical image analysis SME and is also part of the MedIAN Network. |
| Impact | See separate entry |
| Start Year | 2013 |
| Description | Medical Image Understanding and Analysis (MIUA) Conference series |
| Organisation | Medical Image Understanding and Analysis |
| Country | United Kingdom |
| Sector | Learned Society |
| PI Contribution | The MedIAN network provides a complementary function to the national conference in the medical image analysis field (MIUA). In 2017 the network ran a science writing workshop at MIUA 2017, and sponsored the meeting in 2018. |
| Collaborator Contribution | MIUA is the academic national meeting in medical image analysis so connecting with it allows the network to reach out to ECRs/future leaders in the field. |
| Impact | We shared information between the two networks. MedIAN ran a scientific writing event in 2017 and wan an event at the annual conference in 2018. |
| Start Year | 2017 |
| Description | NIHR Cardiovascular HTC |
| Organisation | National Institute for Health Research |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | The NIHR Cardiovascular HTC was a collaborator on the original MedIAN bid. We share information on events between our networks and have run an event together. |
| Collaborator Contribution | We share information on events between our networks and have run an event together. |
| Impact | A joint event was held with follow-up including connecting with the UK Biobank. |
| Start Year | 2014 |
| Description | NIHR Cardiovascular MIC |
| Organisation | National Institute for Health Research |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | The NIHR Cardiovascular MIC replaced the HTC of the same name in January 2018 and we continue to work with them on sharing information and will run a joint meeting in 2018. |
| Collaborator Contribution | See above. |
| Impact | Sharing information and running joint events. |
| Start Year | 2018 |
| Description | NIHR Colorectal HTC |
| Organisation | National Institute for Health Research |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | The NIHR Colorectal Therapies HTC was one of the two HTCs we partnered with initially. Their strength is in identifying new important unmet clinical needs. Leeds based, they also offered us a way to reach out to researchers in this part of the country. |
| Collaborator Contribution | The HTC has advised on activities and suggested members of their network who might be interested in MedIAN. Their HTC was set up before our network and they could offer experience/advice on how to design effective workshops. The HTC ended in 2017 and was superseded by a MIC from January 2018 (see separate entry). |
| Impact | Joint multi-disciplnary collaborations (industry, clinical, academic) in medicine/engineering/physical sciences. |
| Start Year | 2014 |
| Description | NIHR Surgical MedTech Co-operative |
| Organisation | National Institute for Health Research |
| Department | NIHR Surgical MedTech Co-operative |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | The NIHR Colorectal Therapies HTC became the NIHR Surgical MedTech Co-operative in January 2018. We continue to have periodic discussions, plan to hold a joint event in 2018, and share information between our complementary networks. |
| Collaborator Contribution | See above. |
| Impact | Joint events; sharing information between our respective networks. |
| Start Year | 2018 |
| Description | Oxford AHSN |
| Organisation | Oxford Academic Health Science Network |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Sharing of information between complementary networks. |
| Collaborator Contribution | Sharing of information between complementary networks. |
| Impact | Sharing of information about events, funding opportunities etc. |
| Start Year | 2015 |
| Description | Oxford AHSN |
| Organisation | Oxford Academic Health Science Network |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Sharing of information between complementary networks. |
| Collaborator Contribution | Sharing of information between complementary networks. |
| Impact | Sharing of information about events, funding opportunities etc. |
| Start Year | 2015 |
| Description | SINAPSE |
| Organisation | Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | SINAPSE and MedIAN via the MIUA conference which was held in Edinburgh in 2017. |
| Collaborator Contribution | We ran a joint event and SINAPSE contributed to a BigData workshop held in Oxford in 2018. |
| Impact | Agreement to work together on events of mutual interest and share information between our two networks. |
| Start Year | 2017 |
| Description | UK Biobank |
| Organisation | UK Biobank |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | The UK Biobank Imaging consortium is gathering a large amount of image data on study subjects. MedIAN participants have discussed with UK Biobank consortium partners challenges in automated image analysis of the cardiac image data. |
| Collaborator Contribution | Knowledge exchange. Some partners have followed up with UK Biobank to consider how they can support analysis. One example is the SmartHeart Programme Grant. |
| Impact | Individuals followed up from the workshop to consider how they might support the UK Biobank. |
| Start Year | 2016 |
| Title | MULTI-X A cloud-based ecosystem for artificial intelligence in healthcare |
| Description | MULTI-X is a cross-domain research-oriented platform for scalable, collaborative and reproducible computational and data-intensive analysis. This cloud-based framework simplifies the logistical challenges of implementing AI solutions by providing pre-configured environments with ad-hoc scalable computing resources and secures distributed storage, to efficiently build, test, share and reproduce scientific pipelines. MULTI-X is the outcome of more than a decade of technology-driven approaches to support biomedical research; it has been effectively used in large multidisciplinary national and international joint research projects. |
| Type Of Technology | Systems, Materials & Instrumental Engineering |
| Year Produced | 2018 |
| Impact | A major roadblock for AI research in healthcare is enabling access to large-scale and representative multimodal patient and population data. MULTI-X bridges the gap between unmet data analytics needs in healthcare organisations and the data science community by providing a collaborative research ecosystem focused on scalability, portability and reproducibility to streamline prototyping, testing, assessment, and effective deployment of AI solutions. It has been effectively used in different EU funded projects (VPH-DARE, Back-UP) and UK funded grants such as CardioX: integrated and quantitative cardiac imaging reports for Precision Cardiology within LTHT (Grow Medtech). Recently, it has been used to execute a fully automatic workflow for the analysis of cardiac ventricles, trained on a very large set of multi-slice images, and tested and validated on 20.000 subjects of the UK Biobank[1]. [1]Attar, R, Pereañez, M, Gooya, A et al. (13 more authors) (2019) Quantitative CMR population imaging on 20,000 subjects of the UK Biobank imaging study: LV/RV quantification pipeline and its evaluation. Medical Image Analysis, 56. pp. 26-42. ISSN 1361-8415 |
| URL | https://multi-x.org |
| Description | 2nd International Conference on Medical Imaging with Deep Learning (MIDL) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | This new annual conference attracts world leading researchers and engineers from academia, industry and biomedical sciences working at the intersection of medical image analysis and machine learning. The conference series includes three days of oral presentations and poster sessions, and features keynotes from high-profile invited speakers. This conference will be a forum for deep learning researchers, clinicians and healthcare companies to take a leap in the application of deep learning based automatic image analysis in disease screening, diagnosis, prognosis, treatment selection and treatment monitoring. The conference will have a broad scope and include topics such as computer-aided screening and diagnosis, intervention, detection, segmentation, registration, image reconstruction and synthesis. Issues regarding the lack of curated, annotated datasets, noisy reference standards and the high-dimensionality of medical data will be discussed and addressed. Software demonstrations, presentation of medical data sets and innovative clinical applications will also be covered as focus points for integration of deep learning algorithms in clinical practice. |
| Year(s) Of Engagement Activity | 2019 |
| URL | http://2019.midl.io/ |
| Description | BIR/RCR Meeting: AI in Radiology in 2020 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invited talk at the BIR/RCR Annual Meeting on AI in radiology |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www.mybir.org.uk/CPBase__event_detail?id=a173Y00000CwkXhQAJ&site=a0N2000000COvFsEAL |
| Description | British Institute of Radiology Annual Conference - Machine learning for automated reporting using big data, Dr Ali Gooya |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Ali Gooya from the University of Sheffield gave a plenary talk at BIR AC 2016 entitled Machine learning for automated reporting using big data. The main goal was to increase awareness on the role of Machine Learning and Deep Learning in automated medical image analysis and reporting. The audience was very interested in this domain and a number of follow up activities in the network in this space have followed. |
| Year(s) Of Engagement Activity | 2006 |
| URL | https://www.bir.org.uk/education-and-events/annual-congress-2016/ |
| Description | CMIH (Cambridge Centre for Mathematical Imaging Clinic) 1-day Medical Imaging Conference |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | This one day conference brought together those academics working on advances in imaging technology with researchers who investigate new image analysis methods, to help address current challenges. New imaging technology goes side by side with the need for mathematical models to maximise the information gain from these novel imaging techniques. This event presented the opportunity to hear in detail about some of the current project collaborations, and focused on the academic interactions taking place in the field of medical imaging and especially across the EPSRC Centres for Mathematical Sciences in Healthcare. The Programme featured talks that highlighted the role that deep learning can play alongside fundamental mathematical and statistical techniques used in medical imaging, including image analysis and modelling. There was a session for short "elevator pitches" where researchers presented snapshots of their work, which were further explored during a poster exhibition which ran during the lunch and the drinks/networking session. The event was of interest to participants from the biomedical imaging, mathematics, engineering, computer science and physics, as well as biology and medicine. A key aim of the partnerships is the delivery of high quality, multidisciplinary research that will help overcome some of the big challenges facing the NHS. Their remit is to explore how mathematics and statistics can help clinicians to tackle serious health challenges such as cancer, heart disease and antibiotic resistant bacteria. Specifically, researchers will develop new tools from predictive mathematical models to enable earlier diagnosis of chronic diseases such as epilepsy, and new systems to make clinical imaging more accurate and efficient. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://gateway.newton.ac.uk/event/tgmw58 |
| Description | CMIH (Cambridge Centre for Mathematical Imaging Clinic) User Engagement Day |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | MedIAN was able to showcase its aims and form project groups as a result |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.cmih.maths.cam.ac.uk/first-industryuser-engagement-day/ |
| Description | CRUK/EPSRC Early Detection Sandpit - 7 January 2019, Oxford |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invited panel talk & discussion on "AI for Early Detection" - Prof Julia Schnabel |
| Year(s) Of Engagement Activity | 2019 |
| Description | Case CCC Artificial Intelligence in Oncology Symposium |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited keynote on "AI for Cancer Imaging" |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://case.edu/cancer/events/artificial-intelligence-oncology/aio-agenda |
| Description | Clinicians & Academics Knowledge Exchange collaboration with NIHR Cardiovascular MIC (formerly the Cardiovascular HTC) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | The objective of this seminar was to identify areas of real world crossover between research and clinical challenges. One output was that it laid foundations for future collaborative efforts and collectively allowed participants to address and identify unmet clinical challenges that could be addressed and raise new research questions that could be explored and answered together. The 46 clinical imaging attendees reported that the event had broadened their understanding of collaborative processes and unmet needs. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Co-Sponsor of Endoscopy Artefact Detection Challenge EAD2019 at IEEE International Symposium on Biomedical Imaging (ISBI) in Venice, April 8 2019 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The intended purpose of the endoscopy artefact detection challenge to improve patient care and to improve information collection and reusability of endoscopy videos by identifying risks and limitations and workarounds using computer assisted tools. This challenge seeks to engage image analysts within the endoscopic community, clinical endoscopists (who can use the artefact dection algorithm to develop better imaging protocols) and manufacturers/industry members. The primary engagement activity is to improve patient care for clinical endoscopists and AI developers by facilitating diagnosis and treatment of diseases in hollow organs. MedIAN has provided funding to facilitate this challenge to be run in conjunction with the IEEE ISBI in April, 2019 in Venice. Part of this funding went towards supporting travel grants for ECRs travelling to this event. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://biomedicalimaging.org/2019/ |
| Description | Co-organiser of ASMUS2020, a MICCAI workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Advances in Simplifying Medical UltraSound (ASMUS) 2020 is an international workshop that provides a forum for research topics around ultrasound image computing and computer-assisted interventions and robotic systems that utilize ultrasound imaging. It was held in conjunction with MICCAI 2020 in virtual form. The nineteen accepted papers were selected based on their scientific contribution, via a double-blind process involving written reviews from at least two external reviewers in addition to a member of the committee. The published work includes reports across a wide range of methodology, research and clinical applications. Advanced deep learning approaches for anatomy recognition, segmentation, registration and skill assessment are the dominant topics, in addition to ultrasound-specific new approaches in augmented reality and remote assistance. An interesting trend revealed by these papers is the merging of ultrasound probe and surgical instrument localization with robotically assisted guidance to produce increasingly intelligent systems that learn from expert labels and incorporate domain knowledge to enable increasingly sophisticated automation and fine-grained control. Two invited speakers were included in the workshop and the meeting had 80+ attendees. |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://sites.google.com/view/asmus2020 |
| Description | Co-organiser of ASMUS2021, a MICCAI workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Advances in Simplifying Medical UltraSound (ASMUS) 2021 is an international workshop that provides a forum for research topics around ultrasound image computing and computer-assisted interventions and robotic systems that utilize ultrasound imaging. It was held in conjunction with MICCAI 2021 in virtual form. Accepted papers were selected based on their scientific contribution, via a double-blind process involving written reviews from at least two external reviewers in addition to a member of the committee. The published work includes reports across a wide range of methodology, research and clinical applications. Advanced deep learning approaches for anatomy recognition, segmentation, registration and skill assessment are the dominant topics, in addition to ultrasound-specific new approaches in augmented reality and remote assistance. Three invited speakers were included in the workshop, and live demos of technologies were given. The meeting had 80+ attendees. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://miccai-ultrasound.github.io/#/asmus21 |
| Description | Developments in Healthcare Imaging - Connecting with Academia |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | As part of the MedIAN network, we organised a session on Deep Learning in Medical Imaging with selected invited talks from early career researchers and an introduction the network. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://gateway.newton.ac.uk/event/tgmw58/programme |
| Description | Developments in Healthcare Imaging - Connecting with Industry |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | Presented the MedIAN network and invited participants to join the community. |
| Year(s) Of Engagement Activity | 2017 |
| URL | http://www.turing-gateway.cam.ac.uk/event/tgmw48/programme |
| Description | Distinguished Keynote Speaker in Biomedical and Health Data Science in two joint conferences of IEEE EMBS BHI and BSN 2021 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Keynote talk entitled: Simplifying interpretation and acquisition of ultrasound scans, delivered virtually. Abstract: Short Abstract: With the increased availability of low-cost and handheld ultrasound probes, there is interest in simplifying interpretation and acquisition of ultrasound scans through deep-learning based analysis so that ultrasound can be used more widely in healthcare. However, this is not just "all about the algorithm", and successful innovation requires inter-disciplinary thinking and collaborations. In this talk I will overview progress in this area drawing on examples of my laboratory's experiences of working with partners on multi-modal ultrasound imaging, and building assistive algorithms and devices for pregnancy health assessment in high-income and low-and-middle-income country settings. Emerging topics in this area will also be discussed. |
| Year(s) Of Engagement Activity | 2021 |
| Description | ESR Connect |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Live-streamed show on AI in radiology |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://connect.myesr.org/course/use-cases-in-ai-reasons-to-do-ai-with-friends/ |
| Description | East Anglian Radiological Society Annual Meeting (EARS) |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Talk "Hopes and Hurdles for AI in Radiology" |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://radiology.medschl.cam.ac.uk/event/east-anglian-radiological-society-annual-meeting-ears-2019... |
| Description | European Commission Expert Group on Liability and New Technologies |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Policymakers/politicians |
| Results and Impact | Provide the European Commission with expertise on the applicability of the Product Liability Directive to traditional products, new technologies and new societal challenges (Product Liability Directive formation) and assist the Commission in developing principles that can serve as guidelines for possible adaptations of applicable laws at EU and national level relating to new technologies (New Technologies formation). |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://ec.europa.eu/transparency/regexpert/index.cfm?do=groupDetail.groupMeeting&meetingId=9390 |
| Description | Future of Medical Image Analysis workshop (Chester) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invited members of the medical image analysis community attended the workshop to discuss how future networking will happen post the Network grant and a new Network grant application. Lead Prof. Alex Frangi (U. Leeds). |
| Year(s) Of Engagement Activity | 2019 |
| Description | Horizon Europe: New Parliament, new Commission, new agenda |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Policymakers/politicians |
| Results and Impact | Panel discussion: Value-based healthcare: How technologies can improve care across the EU |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://sciencebusiness.net/events/horizon-europe-new-parliament-new-commission-new-agenda |
| Description | IEEE Trans Med Imaging: Special Issue on Simulation and Synthesis in Medical Image Analysis |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | This special issue and accompanying editorial in one of the top journals of our field, introduces the Special Issue on Simulation and Synthesis in Medical Imaging. This special issue was run between Prof AF Frangi and Dr S Tsaftaris (both from UK) and Prof JL Prince (from Johns Hopkins University). In this editorial, we define so-far ambiguous terms of simulation and synthesis in medical imaging. We also briefly discuss the synergistic importance of mechanistic (hypothesis- driven) and phenomenological (data-driven) models of medical image generation. Finally, we introduce the twelve papers published in this issue covering both mechanistic (5) and phenomenological (7) medical image generation. This rich selection of papers covers applications in cardiology, retinopathy, histopathology, neurosciences, and oncology. It also covers all mainstream diagnostic medical imaging modalities. We conclude the editorial with a personal view on the field and highlight some existing challenges and future research opportunities. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://ieee-tmi.org/fast-facts/featured-article.asp?id=28&title=Special-Edition:-Simulation-and-Syn... |
| Description | Imperial Global Science Policy Forum |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Policymakers/politicians |
| Results and Impact | The Imperial Global Science Policy Forum is a high-profile network connecting Imperial academics with senior international science and technology advisers and diplomats, UK government policymakers, industry experts and other relevant stakeholders. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://www.imperial.ac.uk/news/188848/diplomats-industry-leaders-discuss-future-ai/ |
| Description | Importance of benchmarking in medical image analysis and related pitfalls |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future. |
| Year(s) Of Engagement Activity | 2016,2017 |
| Description | International Conference on Image Computing and Computer Assisted Intervention (MICCAI) 2018. Granada, Spain - Program Chair Prof Julia Schnabel |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | This was the largest MICCAI conference to-date, with over 1500 participants from academic and industry. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://miccai2018.org |
| Description | Invited talk at CVPR 2017 workshop |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Gave an invited talk as part of a workshop at CVPR 2017 (Hawaii) which aimed to give an overview to computer vision researchers or problems and state-of-the-art research in medical image analysis. A little follow-up but discussion was quite passive (we might have been competing with the weather on the last day of the meeting!) |
| Year(s) Of Engagement Activity | 2017 |
| Description | MEIbioeng16 Session |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Academic Lead: Alison Noble. Organised and participated in a session on the EPSRC Healthcare Technologies Networks at MEIbioeng16 held in Oxford. Purpose to present the Networks and discuss possible synergies as well as advertise the networks to the conference attendees. |
| Year(s) Of Engagement Activity | 2016 |
| Description | MICCAI16 Challenge |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Sponsored international Challenge at MICCAI 2016 STACOM-SLAWT |
| Year(s) Of Engagement Activity | 2016 |
| URL | http://www.doc.ic.ac.uk/~rkarim/la_lv_framework/wall/index.html |
| Description | MISS Summer School |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited lecturer at international summer school. |
| Year(s) Of Engagement Activity | 2016 |
| Description | MIUA 2021 Conference - co-organiser |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | MIUA is a UK-based international conference for the communication of image processing and analysis research and its application to medical imaging and biomedicine. This was the 25th edition of the meeting which was held virtually. 40 papers were presented (27k downloads as of 09-03-2022). MIUA is the principal UK forum for communicating research progress within the community interested in image analysis applied to medicine and related biological science. The meeting is designed for the dissemination and discussion of research in medical image understanding and analysis, and aims to encourage the growth and raise the profile of this multi-disciplinary field by bringing together the various communities including among others: |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://miua2021.com/ |
| Description | MIUA2020 Conference - co-organiser |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | MIUA is a UK-based international conference for the communication of image processing and analysis research and its application to medical imaging and biomedicine. This was the 24th edition of the meeting which was held virtually. MIUA is the principal UK forum for communicating research progress within the community interested in image analysis applied to medicine and related biological science. The meeting is designed for the dissemination and discussion of research in medical image understanding and analysis, and aims to encourage the growth and raise the profile of this multi-disciplinary field by bringing together the various communities including among others: |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://miua2020.com/ |
| Description | MULTI-X Workshop: A cloud-based ecosystem for AI in Healthcare |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | In this introductory 1-day course, attendees learnt the basic functionalities of MULTI-X and how to use it to: - Develop ML/DL applications using portable and preconfigured virtual environments - Integrate federated datasets into large execution pipelines using on-demand cloud computing resources - Prepare demonstrators to reproduce, visualise and share research outcomes |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://multi-x.org |
| Description | Machine Learning for Translational Medicine & Personalized Healthcare |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Talk "Spot-the-Lesion: Image- based disease detection with deep learning" |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://www.eventbrite.com/e/imperial-college-itmat-dsg-workshop-2019-data-science-challenges-and-op... |
| Description | MedIAN 2 day mini sandpit 2018 and 2019 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Postgraduate students |
| Results and Impact | Sandpits and challenges are fundamental ways to win funding - but there is a lot of competition. This mini sandpit aims to give you the experience of participating in a Sandpit, learn the skills required to improve your chances of success and potentially provide support for one team to take their idea to the next level. The objectives were to build relationships across the network in order to be able to collaborate effectively and generate research proposals that stand out in a competitive environment. The programme support Early Career Researchers to become future leaders in their fields. The scope of the sandpit inquiry process takes a wide focus around bio-medical imaging (and won't necessarily be focused on specific diseases). It looks beyond current horizons to future needs and expands participants' thinking about opportunities. |
| Year(s) Of Engagement Activity | 2018,2019 |
| URL | https://www.median.ac.uk/blog/ |
| Description | MedIAN 2-day Sandpit event for ECRs (April 2019) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Sandpit activity run for approximately 25 ECRs from across the UK. |
| Year(s) Of Engagement Activity | 2019 |
| Description | MedIAN Cardiovascular Scientific Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Academic Leads: Alison Noble, Alex Frangi. MedIAN Cardiovascular workshop that discussed issues in analysis of UK Biobank cardiovascular data. |
| Year(s) Of Engagement Activity | 2016 |
| Description | MedIAN Cardiovascular scientific workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Academic Leads: Alison Noble, Julia Schnabel. A scientific work aimed at engagement between image analysis experts and cardiovascular medicine researchers/clinicians to discuss challenges and new opportunities to work together. Run in collaboration with the NIHR Cardiovascular HTC. Follow-up was meeting to discuss UK Biobank data analysis. |
| Year(s) Of Engagement Activity | 2015 |
| Description | MedIAN CodeFest 2017 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | Academic Lead: Ben Glocker. Approximately 25 people attended including Imperial, UCL, King's and Oxford students but also people from Brighton, Warwick, Cambridge and Buckingham. Two 'challenges' were prepared to work on, a deep learning introduction to analyse brain MRI, and a virtual reality one using the Oculus Rift. Most participants opted for the deep learning one, and the majority came to learn with little prior experience so we had prepared introductory examples in Python and some ideas for example applications (e.g., gender classification, age regression, brain segmentation). Everyone seemed to have a lot of fun, and the group formation worked really well with one or two groups trying to do real research. One group tried to map neural nets to random forests based on a recent paper, and the other group looked into predicting fMRI measurements. Of course, there is very little one can do in just two days, but the social and networking aspects were the focus of the event. Some quotes below from participants: Attendee from Warwick: "It was an amazing experience of learning and working together. The provided sample examples were really helpful to understand and reuse to apply our own idea. In our team one member was really good with coding so we learn to code efficiently from him by modifying existing code with our own idea. I hope, similar events will be organized in future with specific interest in cardiac images." Attendee from Imperial: "Thanks again for a great codefest! Apologies for all my beginner questions, but it has given me a great flying start." |
| Year(s) Of Engagement Activity | 2017 |
| Description | MedIAN Colorectal Scientfic Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Academic Lead: Julia Schnabel, Alex Frangi. Scientific workshop bringing together researchers interested in imaging of colorectal disease held in collaboration with the Colorectal Therapies HTC. |
| Year(s) Of Engagement Activity | 2015 |
| Description | MedIAN website and digital presence |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Academic Lead: Alison Noble. A major activity in 2016/17 was set up a digital resource as the focal point for the MedIAN Network. The public interface of this is located at www.median.ac.uk. The MVP was launched in September 2017 and a further update will be launched in March 2018. The purpose is to provide a focal point for researchers to find out about opportunities and connect with similarly minded professionals to encourage new collaborations in the medical image analysis space. |
| Year(s) Of Engagement Activity | 2017 |
| URL | http://www.median.ac.uk |
| Description | Medical Image Computing and COmputer Assisted Interventions 2018 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Prof Alejandro Frangi is General Chair of MICCAI 2018, the premier international conference in Medical Image Analysis. Several other members of MedIAN contribute this year too: Julia Schnabel as Program Chair, Dan Stoyanov as Workshop Chair, Zeike Taylor as Workshop Co-Chair, etc. This conference has been an opportunity for MedIAN to provide leadership to the community and international exposure. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://www.miccai2018.org |
| Description | Medical Imaging Summer School (MISS 2018): Medical Imaging meets Deep Learning - Director Prof Julia Schnabel |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | The focus of this Medical Imaging Summer School (MISS) is to train a new generation of young scientists to bridge this gap, by providing insights into the various interfaces between medical imaging and deep learning, based on the shared broad categories of medical image computing, computer-aided image interpretation and disease classification. The course will contain a combination of in-depth tutorial-style lectures on fundamental state-of-the-art concepts, followed by accessible yet advanced research lectures using examples and applications. A broad overview of the field will be given, and guided reading groups will complement lectures. The course will be delivered by world renowned experts from both academia and industry, who are working closely at the interface of medical imaging/deep learning. The school aims to provide a stimulating graduate training opportunity for young researchers and Ph.D. students. The participants will benefit from direct interaction with world leaders in medical image computing and deep learning(often working in both fields). Participants will also have the opportunity to present their own research, and to interact with their scientific peers, in a friendly and constructive setting. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://iplab.dmi.unict.it/miss18/ |
| Description | Microsoft Postgraduate Summer School |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited talk at Microsoft Summer school |
| Year(s) Of Engagement Activity | 2016 |
| Description | One day conference "AI in Cardiac Imaging" MedIAN sponsoring travel grants for early career researchers to attend |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | This conference targeted cardiologists and radiologists using or interested in becoming involved with AI approaches to MRI and PET/MRI, biomedical engineers (working in industry and pre- and post-doctoral students) interested in machine learning, and information and data scientists interested in how AI can be used in diagnosis of cardiovascular diseases. This brought together international leaders and researchers in machine learning, computational imaging, cardiac imaging and cardiology and featured high-profile speakers, posters and demonstrations from industry, academia, and clinical settings which all gave an overview of the clinical challenges, and disseminated the latest advances in cardiac imaging and AI, and how these can be combined to create a personalised diagnostic tool for cardiovascular diseases. The intended purpose and outcomes/impact were summed up in the blog one of our travel grant recipients described after the event: "The day covered a wide range of different applications for AI within cardiac imaging - some being at a very early stage, e. g. going directly from MRI raw data to diagnosis, whereas others had been used in thousands of patients. Overall, I am happy that much of the earlier scepticism towards the use of machine learning within cardiac imaging seems to be gone (biased sampling I know...), which allows for those fruitful inter-disciplinary conversations that are necessary before a widespread clinical adoption can take place. " Topics discussed included AI for cardiac image acquisition and reconstruction AI for automated cardiac imaging and QC AI for cardiac image analysis and diagnostics Extracting quantitative biomarkers using AI Mining population and cohort studies using AI Multi-modal (imaging, text, omics) AI approaches AI-based decision support for CVD Explainable and interpretable AI Translation of AI-based solutions into the clinic |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://wp.doc.ic.ac.uk/smartheart/ai-in-cardiac-imaging-workshop |
| Description | Participation in the IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The meeting includes tutorials, challenges and a scientific program composed of plenary talks, invited special sessions, as well as oral and poster presentations of peer-reviewed papers. High-quality papers are presented containing original contributions to the topics of interest including image formation and reconstruction, image processing and analysis, dynamic imaging, visualisation, image quality assessment, machine learning for big image data, and physical, biological, and statistical modelling. Attendance by a broader audience of imaging scientists and clinical professionals is encouraged and additional presentation opportunities are offered thanks to special sessions with specific clinical focus. MedIAN is well represented there to disseminate UK research in medical image analysis, to foster new collaborations and to recruit new talents. |
| Year(s) Of Engagement Activity | 2018,2019 |
| URL | https://biomedicalimaging.org/ |
| Description | Royal Society/Government Chief Scientific Advisors meeting discussing PETs |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Policymakers/politicians |
| Results and Impact | Dinner discussion about PETs and potential future short terms uses of them across government departments. I presented an overview of the policy report that I chaired. |
| Year(s) Of Engagement Activity | 2019 |
| Description | Science Writing Workshop at MIUA 2017 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | MedIAN lead: David Johns (Digital Communications Officer). An activity aimed at promoting awareness of the MedIAN network and its activities and ambitions held at the national Medical Image Understanding and Analysis conference. Comments from scientific writing workshop: "I really liked the clarity of the concept of a scientific blog and the explanation of the differences from a publication" "[I liked the] tricks and strategies for writing (list of things you do)" "I got everything I wanted out of it, can't really think of a way to improve it |
| Year(s) Of Engagement Activity | 2017 |
| Description | Speaker - International Women in Engineering Day 2017 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | Secondary school girls from a number of local schools visited the department to see different areas of engineering and do some simple activities related to engineering. I gave the short talk at tea on some of emerging areas of engineering (wacky engineering) and talked a little about my own research and my field. Feedback from schools was positive for the whole event. |
| Year(s) Of Engagement Activity | 2017 |
| Description | Sponsored 22nd conference on Medical Image Understanding and Analysis 2018 (MIUA) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Medical Image Understanding and Analysis (MIUA) is a UK-based meeting for the communication of research related to image analysis and its application to medical imaging and biomedicine. The meetings provide an opportunity to present and discuss research in medical image understanding and analysis; a rapidly growing subject with ever increasing real-world applicability. MIUA is collaborated with the BMVA. Medical Image understanding is an intrinsically interdisciplinary activity, drawing on expertise from computer science, engineering, physics, clinical practice and fundamental bioscience. Many researchers with an interest in MIUA topics will also belong to wider communities in each of these disciplines, which overlap, but are not congruent with, the MIUA community. The 22nd Annual Conference in Medical Image Understanding and Analysis (MIUA 2018) was held at the University of Southampton. MIUA is a UK-based meeting for the communication of research related to image analysis and its application to medical imaging and biomedicine. The meetings provide an opportunity to present and discuss research in medical image understanding and analysis; a rapidly growing subject with ever increasing real-world applicability. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://miua2018.soton.ac.uk/ |
| Description | Teamwork skills for Early Career Researchers |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Other audiences |
| Results and Impact | This 2 day workshop was aimed at Early Career Researchers: "to understand what type of worker you are and how you interact with others enabling you to engage in collaboration in an effective way. You will learn skills and techniques to support the dissemination of ideas within a group setting and how to communicate effectively." |
| Year(s) Of Engagement Activity | 2020 |
| Description | The Future of UK Medical Image Analysis - funding event |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | 2-day residential workshop entitled "The Future of UK Medical Image Analysis" to be held in Chester on 30 April and 1st May 2019. The purpose of the workshop is to bring together leading figures in the UK medical image analysis community to discuss challenges facing our rapidly changing and growing field, to identify areas of future growth and opportunity in research and translation on a 5-10 year timescale, and to consider ways in which we can encourage greater networking and collaboration between more UK groups. The primary output of the residential workshop will be a published report, and hopefully you will personally benefit from meeting some new professional acquaintances with shared research interests. " |
| Year(s) Of Engagement Activity | 2019 |
| Description | The Medical Image Analysis Network (MedIAN) website, twitter account (MedIAN_UK) and Linkedin group MedIAN - Medical Imaging Analysis Network UK |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | The website and supporting outlets of social media were set up to engage and embed the medical imaging community. The website has event and blog features which can advertise relevant areas of interest to its members. Twitter can react to current events and member successes whilst reminding participants about call for paper dates, available travel grants and easily forge collaborations with similarly-minded groups in the ML, AI and imaging sectors. The Linkedin group was just to engage the members further; and mop up any stray clinicians, academics, and industry professionals working in medical image analysis. By signing up for a profile they can post announcements, opportunities, questions, and call-outs with the community, and contact other members directly. In this way, the network can be self sustained. |
| Year(s) Of Engagement Activity | 2018,2019 |
| URL | https://www.median.ac.uk |
| Description | Tutorial on Deep Learning for Medical Imaging at MICCAI 2018 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | This half-day tutorial covered important aspects of deep learning with a particular focus on medical imaging applications. The tutorial aimed to provide an introduction to the basics and fundamental concepts of deep learning, practical advice for the use of deep learning for medical imaging tasks, and gave an overview of latest developments and opportunities for future research. The tutorial was targeted at all levels and for any researcher interested in deep learning. The first lectures were tailored for people new to the field (e.g., first year PhD students), while later lectures covered more advanced topics and latest developments which should be of interest to anyone already working with deep learning methods. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://sites.google.com/view/miccai-dl-tutorial |
| Description | UCL Partners AHSC Cardiovasvcular eMedLab Workshop |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | This meeting had as purpose to bring together people working on the UK Biobank Data specially those with a technical focus working either on image analysis or data management. The group in Sheffield presented the work they are doing on cardiac image analysis and their work on www.multi-x.org. The work was very well received and we have currently a paper on quality assessment that is under review and whose origins could be traced back to discussions in this meeting with QMUL and Oxford colleagues. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://uclpartners.com/events/cardiovascular-emedlab-workshop/ |