In vivo digital retinal pathology: imaging retina with molecular specific contrast and cellular resolution

点击翻译按钮获取中文摘要

The overarching goal of my research program is to develop novel imaging tools and technology for in vivo retinal imaging which will enable dynamic cellular and molecular analysis of disease mechanism in living animal models. These advanced bio-microscopic tools have potential to contribute not only to the development of regenerative medicine and stem cell therapies, but also to generate novel concepts for high resolution microscopy. Objective 1. The principle aim of my research program is to develop and advance Visible light All-in-One (VAiO) retinal imaging technology that comprises a retinal Optical Coherence Tomography (OCT) system with visible light illumination, Adaptive Optics (AO), and Polarization Diversity Detection (PDD). Using VAiO-OCT the morphological detail of individual retinal layers will be visualized with multiple optical contrasts at a 3D isotropic cellular resolution to enable non-invasive dynamic retinal molecular imaging capabilities. Objective 2. A complementary second objective of my research program is to develop novel computational image analysis and machine learning tools that are tailored specifically for digital retinal pathology. By clustering pixels based on their spatial proximity and multiple optical feature similarity, a digital `stain' for retinal tissues from VAiO-OCT image can be achieved, which would be useful for highlighting different tissue groups inside of the retina and enhance their contrast. This objective will achieve predictive modeling of retinal pathology images from a detection, segmentation, feature extraction, and tissue classification perspective.