Deep learning for glaucoma detection

Glaucoma is the second leading cause of blindness in the world, impacting approximately 2.7 million people in the U.S alone. It is a complex set of diseases and, if left untreated, can lead to blindness. It's a particularly large issue in Australia, where only 50 percent of all people who have it are actually diagnosed and receive the treatment they need. As part of a team of scientists from IBM and New York University, my colleagues and I are looking at new ways AI could be used to help ophthalmologists and optometrists further utilize eye images, and potentially help to speed the process for detecting glaucoma in images. In a recent paper, we detail a new deep learning framework that detects glaucoma directly from raw optical coherence tomographic (OCT) imaging, a method which uses light waves to take cross-section pictures of the retina.