CAD WALK · Enabling Computer Aided Diagnosis of Foot Pathologies through the use of Metric Learning
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2017-10-01 → 2019-09-30
- EU contribution
- €160,800
- Participants
- 1
- Scheme
- MSCA-IF-EF-ST
Lines connect the coordinator with its partners.
Results in brief
CAD WALK: Enabling Computer Aided Diagnosis of Foot Pathologies through the use of Metric Learning
It is estimated that anywhere between 17-41% of the general population experience foot pain and, in roughly half of these cases, the foot pain is disabling. Nevertheless, the majority of those with foot pain do not seek professional treatment. These statistics have been interpreted in the research field as a need for improving foot diagnosis techniques. One tool that has shown potential in diagnosing foot problems is dynamic plantar pressure imaging. This technique measures, across time, the pressures that the bottom (plantar) surface of a person’s foot makes with the ground. From these plantar pressure videos, a clinician will attempt to identify pressure abnormalities and develop a personalized treatment strategy. Unfortunately, plantar pressure imaging creates large, dynamic, datasets with tens of thousands of sampled pressure values. These datasets cannot be easily analyzed and interpreted by the human brain. As a result, clinicians typically base their diagnoses on visual inspection of a small amount of this pressure data. By examining only a subset of the pressure video, it is possible that potentially valuable diagnostic information may be ignored. We believe that a computer-aided diagnosis (CAD) system could efficiently assist clinicians in the analysis of full plantar pressure videos, thereby making sure that the diagnostic potential of plantar pressure imaging is fully exploited. To test this idea, we began this CAD WALK project with the goal of developing a CAD system for plantar pressure videos within a two-year time frame. The CAD WALK system follows a basic principle: given an individual’s plantar pressure video, we will compare that video to one taken from the individuals “healthy identical twin”. If any differences in plantar pressures are found, then they must be related to the foot problem the individual is experiencing and should therefore be highlighted. Unfortunately for us, most people don’t have an identical twin, so we require a technique that will allow us to estimate their measurement. Overall, the aims of the CAD WALK project can be listed as (a) the estimation of healthy plantar pressure videos from an individual’s demographic characteristics, (b) the use of these estimates in a CAD system to highlight plantar pressures that are abnormal, and (c) the creation of a commercial product out of this CAD system.
Data: CORDIS, © European Union
Project objective
Dynamic plantar pressure imaging (PPI) refers to the measuring, across time, of pressure fields between the foot and the ground. PPI is used, in part, to diagnose foot problems such as metatarsalgia and plantar fasciitis. Despite the widespread clinical use of PPI, its diagnostic potential has not been fully exploited. PPI creates large and dynamic datasets that cannot be easily analysed and interpreted by the human brain. As a result, PPI images are subsampled before being clinically examined, which discards potentially valuable information.The objective for this action is to improve the diagnostic value of PPI through the introduction of a computer-aided diagnosis (CAD) system called CAD WALK. Using concepts from my previous CAD research (STEAM), CAD WALK will build a statistical model of PPI images from a healthy population. To test a new patient, their PPI image will be aligned to the model and compared to that healthy population using statistical tests. Outliers from these statistical tests will then be highlighted to help guide a clinician’s examination of the full PPI image. As a novel addition, metric learning will be introduced to create a statistical model that is more specific to the test subject.A key goal of this action is the deployment of CAD WALK as a supported software product. To do so, we propose a Triple ‘i’ (international, intersectoral, interdisciplinary) initiative that partners me with industry (rs scan®) and clinical end users (Sint Maartenskliniek, NL) to translate my CAD research into practical use. Through this process, and a secondment with industry partner rs scan®, I expect to deepen my knowledge of industrial product development (i.e. intellectual property rights, industry regulations, customer constraints) and improve my management skills. By addressing these two gaps in my career experience, I expect to move one step closer to fulfilling my ambition of leading my own research translation lab.
Original text from CORDIS.
Participants
- UNIVERSITEIT ANTWERPEN · AntwerpenCoordinatorBelgium
Links
Data: CORDIS, © European Union