Computer Aided Diagnostic System for Cardiovascular Disease
Lead Research Organisation:
Imperial College London
Department Name: Computing
Abstract
My current PhD research topic is focused on creating a decision support system for radiologists that can facilitate the diagnostic process without the need for labeled data. Our aim is to use past radiological exams (in various modalities, including X-rays and MRI) and their corresponding reports (created by clinicians as part of the normal protocol within a hospital)and develop a learning framework that can learn the correspondence between the image regions and parts of the report and be able to automate the process of generating these reports.
Organisations
People |
ORCID iD |
| Daniel Rueckert (Primary Supervisor) | |
| Aydan Gasimova (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509486/1 | 01/10/2016 | 31/03/2022 | |||
| 1791460 | Studentship | EP/N509486/1 | 01/10/2016 | 30/06/2020 | Aydan Gasimova |
| Description | Computer aided diagnostic system that can auto-generated radiological reports for chest x-ray images |
| Exploitation Route | The system to auto-generate reports for chest X-ray images can be taken further and improved by, for instance, being used by radiologists as part of a validation study where they incorporate it into their work-flow and report error/issues on the fly so that the algorithm can be improved (as part of a manual adjustment process, or in an automated way whereby the model can continuously update when it is corrected by a radiologist). |
| Sectors | Healthcare |