Using A Cropping Technique or Not: Impacts on SVM-based AMD Detection on OCT Images

Abstract

This paper compares the system performance of distinct flows with automatic image cropping to without automatic image cropping for age-related macular degeneration (AMD) detection on optical coherence tomography (OCT) images. Using the image cropping, the computational time of noise removal and feature extraction can be significantly reduced by a small loss of detection accuracy. The simulation results show that using the image cropping at the first stage achieves 93.4% accuracy. Compared to the flow without image cropping, using the image cropping loses only 0.5% accuracy but saves about 12 hours computational time and about a half of memory storages.