MOPED Follow On
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Physics and Astronomy
Abstract
The University of Edinburgh's Blackford Analysis team, based at the Institute for Astronomy, has developed an advanced software tool for Magnetic Resonance Imaging (MRI) scanning which corrects movement and enhances and improves images by removing the requirement for the patient to remain entirely still for the duration of the scan. Movement renders one tenth of all scans either partially corrupted or totally unusable, wasting £120,000 per scanner each year. This totals to £30 million of wasted scans per year in the UK and greater than £1.3 billion worldwide. At the heart of the technology is the patented MOPED algorithm, which can remove these motion artefacts in real-time, resulting in high quality images suitable for diagnosis which could not otherwise have been obtained. Importantly, this technology enables MRI scanning for severely ill patients and young children who cannot remain still without sedation, and further brings advanced imaging techniques, formerly only possible in a research environment, into routine clinical use. The strategy is to spin out a company, Blackford Analysis, which will initially sell to research organisations and then license its existing software to large MRI manufacturers. This will sustain a high growth company providing other solutions based on applications developed using the MOPED algorithm platform. The underlying technology platform has been demonstrated in other areas, with successful application to spectral analysis and image processing in astrophysics. The Company will expand to data analysis problems in the medical field and beyond through a pipeline of further products addressing facial recognition, hyperspectral imaging and industrial quality control. The University of Edinburgh will grant Blackford Analysis exclusive worldwide rights on the intellectual property, with freedom to develop further application areas as they become apparent. The Blackford Analysis team consists of experienced clinicians and physicists designing algorithms and writing software to a quality system designed to be compatible with an ISO 9000:2001 regime compliant with the requirements of the FDA and for CE approval. A prototype of the technology, suitable for presentations, is already in place and further development is underway to produce a software package which can be used to benchmark against existing techniques. Interest from luminary clinicians and major manufacturers has been secured. Resources from the Follow on Fund would be used to further the development of the medical imaging application, and exploration of other applications based on the MOPED algorithm, via market studies and technical development.
People |
ORCID iD |
Alan Heavens (Principal Investigator) | |
Ben Panter (Researcher) |
Description | THALES consultancy |
Organisation | Thales Group |
Country | France |
Sector | Private |
PI Contribution | Commercially sensitive |
Collaborator Contribution | Identified possible future applications for the technology developed during the grant. |
Impact | Commercially sensitive |
Start Year | 2010 |
Title | PROCESS AND APPARATUS |
Description | The present invention relates to a process of bringing at least one subject data set into registration or conformity with a reference data set by electronic methods, each data set being a representation of a respective object. The process comprises: generating each of a plurality of candidate data sets (32) by applying a transformation to a reference data set, the transformation having predetermined variables that are changed such that each of the plurality of candidate data sets is a differently shifted or distorted reference data set; compressing each of the plurality of candidate data sets (34) to form a respective compressed candidate data set and compressing a subject data set (36) to form a compressed subject data set, the step of compressing comprising: determining a plurality of weighting vectors in dependence upon the predetermined variables, the number of weighting vectors being equal to the number of predetermined variables; multiplying all data in a candidate or subject data set by each weighting vector to provide respective, corresponding data elements of the compressed candidate or subject data set; comparing the compressed subject data set with each of the compressed candidate data sets and, in dependence on the comparisons, determining the transformation that has generated the candidate data set corresponding to the compressed candidate data set, which, of the plurality of compressed candidate data sets, provides a best match with the compressed subject data set (38, 40); and applying an inverse of the determined transformation to the subject data set (42). |
IP Reference | US2010202709 |
Protection | Patent granted |
Year Protection Granted | 2010 |
Licensed | Commercial In Confidence |
Impact | N/A |
Title | PROCESS AND APPARATUS |
Description | The present invention relates to a process of bringing at least one subject data set into registration or conformity with a reference data set by electronic methods, each data set being a representation of a respective object. The process comprises: generating each of a plurality of candidate data sets (32) by applying a transformation to a reference data set, the transformation having predetermined variables that are changed such that each of the plurality of candidate data sets is a differently shifted or distorted reference data set; compressing each of the plurality of candidate data sets (34) to form a respective compressed candidate data set and compressing a subject data set (36) to form a compressed subject data set, the step of compressing comprising: determining a plurality of weighting vectors in dependence upon the predetermined variables, the number of weighting vectors being equal to the number of predetermined variables; multiplying all data in a candidate or subject data set by each weighting vector to provide respective, corresponding data elements of the compressed candidate or subject data set; comparing the compressed subject data set with each of the compressed candidate data sets and, in dependence on the comparisons, determining the transformation that has generated the candidate data set corresponding to the compressed candidate data set, which, of the plurality of compressed candidate data sets, provides a best match with the compressed subject data set (38, 40); and applying an inverse of the determined transformation to the subject data set (42). |
IP Reference | US2010202709 |
Protection | Patent granted |
Year Protection Granted | 2010 |
Licensed | Commercial In Confidence |
Impact | N/A |
Description | Science and the Parliament |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | Yes |
Primary Audience | Policymakers/politicians |
Results and Impact | 40 scientists, industrialists, health care professionals and policymakers attended. Exposure for Blackford Analysis spin out. |
Year(s) Of Engagement Activity | 2009 |