Fovea and optic disk detection and key performance indicators process automation

Abstract

This work, integrated in Critical Health, presents a new process to detect fovea and optic disk in retinal images and the application of some technologies to do the automation of Key Performance Indicators process (KPI). The proposed method consists in ve steps: selection of an area in the image where the optic disk is located using Sobel operator, extraction of optic disk boundaries applying the Hough transform to detect center and diameter of optic disk, detection of the ROI (region of interest) where the fovea is located based on the optic disk center and its diameter and detection of the fovea within the ROI. The developed algorithm has been tested in a proprietary dataset with 1464 images (with ground truth generated by experts) and with some public datasets. Retmarker is an image processing product developed by Critical Health. The KPI is a process implemented in Critical Health to test Retmarker with the goal to reach the optimal performance. This process is currently highly manual and performed on a weekly basis, demanding a considerable amount of man-hours per year. A new plan was implemented to make this process fully automated. Keywords: Biomedical image processing, Digital images, Filtering, Image segmentation, Anatomical structure, Automation, Database systems.