Adaptive Optics for Medical Imaging

1) Brief description of the context of the research including the potential impact
This research project is in biomedical optical imaging, and primarily on a technique called optical coherence tomography (OCT). The target application is medical imaging of the retina, the light sensitive tissue at the back of the eye. OCT is a commonly used technique to diagnose diseases causing vision loss. The purpose of this research project is to improve diagnostic capabilities by improving the resolution of the imaging system and advancing the analysis of the images acquired. The research will include the development of complete OCT systems, including optical hardware (lenses, fibre optics, photodetectors), and control software (coordinating the camera, processing, and display) for medical image acquisition. This project also includes the combination of adaptive optics (AO) with OCT, for the purpose of enhancing the sharpness of the images to enable the cells in the retina to be resolved. Post-acquisition processing of the images will be performed to identify biomarkers of retinal diseases in the high-resolution images. The OCT images that are acquired will be processed using conventional programming as well as Deep Learning methods for feature identification and for diagnostic classification of healthy and diseased eyes. Cellular resolution imaging and image analysis are also important in the evaluation of novel regenerative therapy and have significant potential to accelerate clinical trials by providing detailed feedback on the effects of the new therapy. The images will provide indications if the targeted cell types are present in the retina, and if they are functioning correctly.
2) Aims and Objectives
The aim of this project is to develop a novel biomedical optical imaging system OCT with resolution enhancement technologies like Adaptive Optics and machine learning. The resulting high-resolution imaging in the eye non-invasively will permit the visualization of the retina with cellular resolution. This is significant for the identification of disease progression in the early phases before noticeable and irreversible loss of vision occurs.
3) Novelty of Research Methodology
The research methodology uniquely integrates Adaptive Optics (AO) with Optical Coherence Tomography (OCT), presenting a novel approach to amplify image clarity. This integration brings the minute cellular structures of the retina into sharp focus, surpassing traditional imaging capabilities. Additionally, the introduction of Deep Learning techniques to OCT image analysis represents a significant advancement. With artificial intelligence, the methodology enhances the depth and accuracy of the diagnostic tool, enabling the detection of intricate retinal patterns that were previously undetectable using conventional methods.
4) Alignment to EPSRC's strategies and research areas
The project focuses on the enhancement of Optical Coherence Tomography (OCT) through the integration of Adaptive Optics (AO) and Deep Learning techniques, which aligns with EPSRC's commitment to world-leading and transformative research in the engineering and physical sciences. The project's interdisciplinary blend of optics, computation, and clinical applications embodies EPSRC's vision of fostering cross-disciplinary collaborations to address complex challenges.
5) Any companies or collaborators involved
The NIHR BRC at Moorfields and UCL Institute of Ophthalmology is a co-funder of this research project and will provide additional research infrastructure toward the completion of the objectives.