We are interested in segmenting key pathologic features of age-related macular degeneration (AMD) in clinical retinal images that are routinely obtained in clinic. In particular, we are using optical coherence tomography (OCT) images combined with near-infrared reflectance (NIR) images to follow the many disease features of AMD. Many of these features are similar in appearance, and a key distinction is determining whether a feature represents the presence of a positive pathologic characteristic or the absence of normal tissue. We have provided clinical perspectives and ideas to those in Operations Engineering and Computer Science working on such questions.
I am a physician-scientist with a bench science lab dedicated to the basic pathobiology of age-related macular degeneration (AMD). However, as a practicing clinician seeing AMD patients and routinely obtaining retinal clinical imaging of such patients, I also have a strong interest in understanding AMD pathological features from these images. Understanding the evolution of such features, and then tying those imaging features to basic biology of the retina obtained in the lab, adds significant insight into AMD pathogenesis. I don't have the engineering or computer vision capacity, but have worked well with those in this arena to ask and address critical needs to analyzing clinical retinal images.