Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation.
Journal:
IEEE transactions on bio-medical engineering
Published Date:
Apr 19, 2018
Abstract
OBJECTIVE: Deep learning based methods for retinal vessel segmentation are usually trained based on pixel-wise losses, which treat all vessel pixels with equal importance in pixel-to-pixel matching between a predicted probability map and the corresponding manually annotated segmentation. However, due to the highly imbalanced pixel ratio between thick and thin vessels in fundus images, a pixel-wise loss would limit deep learning models to learn features for accurate segmentation of thin vessels, which is an important task for clinical diagnosis of eye-related diseases.