Ellipse Meets Bit-Planes: A Novel Approach to RNFL based Glaucoma Detection Using Advanced Image Processing and Deep Learning
Researchers have developed a new pipeline for automatic glaucoma detection using color fundus images. The approach utilizes an adaptive algorithm for ellipse-based polar transformation to analyze the Retinal Nerve Fiber Layer (RNFL), a key biomarker for glaucoma. Two frameworks were introduced: one deep learning-inspired feature fusion approach achieving 99.3% detection rate, and a bit-plane slicing image-processing algorithm offering 92.31% accuracy for faster inference. AI