Researchers at the U.S. National Institutes of Health (NIH) have made a groundbreaking advancement in retinal imaging by harnessing the power of artificial intelligence (AI). According to the NIH, this new AI-driven method accelerates imaging processes by 100 times and enhances image contrast by 3.5-fold.
\"Artificial intelligence helps overcome a key limitation of imaging cells in the retina, which is time,\" said Johnny Tam, leader of the Clinical and Translational Imaging Section at NIH's National Eye Institute.
Tam is developing a technology called adaptive optics (AO) to enhance imaging devices based on optical coherence tomography (OCT). OCT, similar to ultrasound, is a noninvasive, quick, and painless procedure and is standard equipment in most eye clinics.
The team introduced a novel AI-based method known as the parallel discriminator generative adverbial network (P-GAN), a deep learning algorithm. By training the P-GAN network with nearly 6,000 manually analyzed AO-OCT-acquired images of the human retinal pigment epithelium, the team enabled the network to identify and recover speckle-obscured cellular features.
This significant improvement offers researchers a superior tool to evaluate age-related macular degeneration and other retinal diseases more effectively.
Reference(s):
cgtn.com
