DETECTING AVASCULAR AND SIGNAL REDUCTION AREAS IN RETINAS USING NEURAL NETWORKS

摘要

This disclosure describes systems, devices, and techniques for training neural networks to identify avascular and signal reduction areas of Optical Coherence Tomography Angiography (OCTA) images and for using trained neural networks. By identifying signal reduction areas in OCTA images, the avascular areas can be detected with high accuracy, even when the OCTA images include artifacts and other types of noise. Accordingly, various implementations described herein can accurately identify avascular areas from real-world clinical OCTA images. In various implementations, a method can include identifying images of retinas. The images may include thickness images, reflectance intensity maps, and OCTA images of the retinas. Avascular maps corresponding to the OCTA images can be identified. A neural network can be trained based on the images and the avascular maps.