Fully Automatic Segmentation and Assessment of Atrial Scars for Atrial Fibrillation Patients Using LGE MRI
Lead Research Organisation:
Imperial College London
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
The main objectives of this proposal are to (1) develop a novel data harmonisation method based on recently proposed domain adaptation and generative adversarial models; (2) carry out an initial two-centre cross-national validation study on the retrospectively collected LGE MRI data; (3) independent testing of a multicentre study consists of data collected from four centres, i.e., Brompton (UK), Anam (South Korea), KCL (UK), and Utah (USA), where the data from KCL and Utah are with open access; (4) strengthen further teaching, training and research collaboration links between UK and South Korea clinicians and technicians to gain more understanding about LGE MRI data and deep learning based fibrosis assessment; and (5) enable large-scale basic science and technical development projects and prospective clinical trials at two nations and further international studies.
Publications
Zhu J
(2023)
Non-invasive prediction of overall survival time for glioblastoma multiforme patients based on multimodal MRI radiomics
in International Journal of Imaging Systems and Technology
Zhou X
(2022)
AI-based medical e-diagnosis for fast and automatic ventricular volume measurement in patients with normal pressure hydrocephalus.
in Neural computing & applications
Zhao X
(2023)
GLRP : Global and local contrastive learning based on relative position for medical image segmentation on cardiac MRI
in International Journal of Imaging Systems and Technology
Zhao B
(2023)
Prompt learning for metonymy resolution: Enhancing performance with internal prior knowledge of pre-trained language models
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Zhao B
(2023)
ChatAgri: Exploring potentials of ChatGPT on cross-linguistic agricultural text classification
in Neurocomputing
Zhang W
(2021)
ME-Net : Multi-encoder net framework for brain tumor segmentation
in International Journal of Imaging Systems and Technology
Zhang W
(2021)
Multi-task learning with Multi-view Weighted Fusion Attention for artery-specific calcification analysis
in Information Fusion
Zhang W
(2023)
Multiple Adversarial Learning Based Angiography Reconstruction for Ultra-Low-Dose Contrast Medium CT.
in IEEE journal of biomedical and health informatics
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(2021)
Multitask Learning for Estimating Multitype Cardiac Indices in MRI and CT Based on Adversarial Reverse Mapping
in IEEE Transactions on Neural Networks and Learning Systems
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(2022)
Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation
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(2022)
Quantification of changes in white matter tract fibers in idiopathic normal pressure hydrocephalus based on diffusion spectrum imaging.
in European journal of radiology
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(2022)
Quantifying the impact of Pyramid Squeeze Attention mechanism and filtering approaches on Alzheimer's disease classification.
in Computers in biology and medicine
Xing X
(2023)
HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis.
in IEEE journal of biomedical and health informatics
Xing X
(2023)
Less Is More: Unsupervised Mask-Guided Annotated CT Image Synthesis With Minimum Manual Segmentations.
in IEEE transactions on medical imaging
Wu Y
(2021)
Fast and Automated Segmentation for the Three-Directional Multi-Slice Cine Myocardial Velocity Mapping.
in Diagnostics (Basel, Switzerland)
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(2023)
Vehicular Abandoned Object Detection Based on VANET and Edge AI in Road Scenes
in IEEE Transactions on Intelligent Transportation Systems
Wang C
(2021)
Industrial Cyber-Physical Systems-Based Cloud IoT Edge for Federated Heterogeneous Distillation
in IEEE Transactions on Industrial Informatics
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(2022)
Unsupervised Image Registration towards Enhancing Performance and Explainability in Cardiac and Brain Image Analysis.
in Sensors (Basel, Switzerland)
Tang Z
(2023)
Adversarial Transformer for Repairing Human Airway Segmentation.
in IEEE journal of biomedical and health informatics
Shi Z
(2024)
MLC: Multi-level consistency learning for semi-supervised left atrium segmentation
in Expert Systems with Applications
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(2024)
CCheXR-Attention : Clinical concept extraction and chest x-ray reports classification using modified Mogrifier and bidirectional LSTM with multihead attention
in International Journal of Imaging Systems and Technology
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Focus on machine learning models in medical imaging.
in Physics in medicine and biology
Papanastasiou G
(2023)
Large-scale deep learning analysis to identify adult patients at risk for combined and common variable immunodeficiencies
in Communications Medicine
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(2023)
Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation.
in IEEE transactions on neural networks and learning systems
Nan Y
(2022)
Unsupervised Tissue Segmentation via Deep Constrained Gaussian Network.
in IEEE transactions on medical imaging
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(2022)
Automatic fine-grained glomerular lesion recognition in kidney pathology
in Pattern Recognition
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Automatic COVID-19 and Common-Acquired Pneumonia Diagnosis Using Chest CT Scans
in Bioengineering
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(2022)
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in Frontiers in Medicine
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(2021)
PIC-GAN: A Parallel Imaging Coupled Generative Adversarial Network for Accelerated Multi-Channel MRI Reconstruction.
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(2021)
Which GAN? A comparative study of generative adversarial network-based fast MRI reconstruction.
in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
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(2021)
Transfer learning enhanced generative adversarial networks for multi-channel MRI reconstruction.
in Computers in biology and medicine
Lu S
(2024)
Dual consistency regularization with subjective logic for semi-supervised medical image segmentation
in Computers in Biology and Medicine
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(2021)
Deep Learning Enables Prostate MRI Segmentation: A Large Cohort Evaluation With Inter-Rater Variability Analysis.
in Frontiers in oncology
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(2024)
A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes
in American Journal of Neuroradiology
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(2022)
Physiologically personalized coronary blood flow model to improve the estimation of noninvasive fractional flow reserve.
in Medical physics
Liu X
(2023)
Motion estimation based on projective information disentanglement for 3D reconstruction of rotational coronary angiography
in Computers in Biology and Medicine
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(2023)
Global Transformer and Dual Local Attention Network via Deep-Shallow Hierarchical Feature Fusion for Retinal Vessel Segmentation.
in IEEE transactions on cybernetics
Li M
(2023)
Explainable COVID-19 Infections Identification and Delineation Using Calibrated Pseudo Labels
in IEEE Transactions on Emerging Topics in Computational Intelligence
Description | Cambridge Mathematics of Information in Healthcare Hub |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Department | Centre for Mathematical Imaging in Healthcare |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | Developing new collaborations working on MRI denoising models. |
Collaborator Contribution | Prof Carola-Bibiane Schönlieb and Dr Angelica I. Aviles-Rivero provide guidance and intellectual knowledge input for my PhD student Jiahao Huang via this collaboration. We have regular research meetings and we have joint publications under submission. |
Impact | Currently, one conference paper is under review and one journal paper is under submission. |
Start Year | 2022 |
Description | Collaboration with Prof Sung Ho Hwang and Dr Yongwon Cho at Korea University Anam Hospital |
Organisation | Korea University |
Country | Korea, Republic of |
Sector | Academic/University |
PI Contribution | This project supports our collaboration with Prof Sung Ho Hwang and Dr Yongwon Cho at Korea University Anam Hospital to research into multicentre and multinational LGE CMR data. |
Collaborator Contribution | We have on-going discussions and efforts on building up a multicentre and multinational LGE CMR database. |
Impact | Publications in preparation. |
Start Year | 2021 |
Description | Prof. Pietro Lio (Cambridge University) on super-resolution for cardiac images |
Organisation | University of Cambridge |
Department | Computer Laboratory |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We work with Prof. Pietro Lio (Cambridge University) for solving the super-resolution for cardiac images. |
Collaborator Contribution | Prof. Pietro Lio has expertise in bioinformatics, computational biology models and machine learning, and research studies in integrating various types of data (molecular and clinical, drugs, social and lifestyle) across different spatial and temporal scales of biological complexity to address personalised and precision medicine. Prof. Pietro Lio has contributed his knowledge in our research studies and helped us designed novel super-resolution techniques for cardiac images. He has also provided us guidance and support for our further funding applications. |
Impact | This collaboration is multi-disciplinary. Prof Pietro Lio has got expertise in medical image analysis. Zhu, Jin, Chuan Tan, Junwei Yang, Guang Yang, and Pietro Lio'. "Arbitrary scale super-resolution for medical images." International Journal of Neural Systems 31, no. 10 (2021): 2150037. Jin Zhu, Guang Yang, Tom Wong, Raad Mohiaddin, David Firmin, Jennifer Keegan, and Pietro Lio. A Single-Image Super-Resolution Method for Late Gadolinium Enhance- ment CMR. In the International Society for Magnetic Resonance in Medicine 27th Annual Meeting (ISMRM) 2019 Jin Zhu, Guang Yang, Pedro Ferreira, Andrew Scott, Sonia Nielles-Vallespin, Jennifer Keegan, Dudley Pennell, Pietro Lio, and David Firmin. A ROI Focused Multi-Scale Super- Resolution Method for the Di usion Tensor Cardiac Magnetic Resonance. In the International Society for Magnetic Resonance in Medicine 27th Annual Meeting (ISMRM) 2019 |
Start Year | 2018 |