A Novel Weakly Supervised Multitask Architecture for Retinal Lesions Segmentation on Fundus Images скачать в хорошем качестве

A Novel Weakly Supervised Multitask Architecture for Retinal Lesions Segmentation on Fundus Images

👇Download Article👇 https://www.ijert.org/a-novel-weakly-... IJERTV9IS050205 A Novel Weakly Supervised Multitask Architecture for Retinal Lesions Segmentation on Fundus Images Mukkupogu Praveen , Thameem Ansari , Pabba Vamshi , Ravi Shankar Mishra The first step towards an automated diagnosis tool for retinopathy that is interpretable in its decision-making. However, the limited availability of ground truth lesion detection maps at a pixel level restricts the ability of deep segmentation neural networks to generalize over large databases. In this paper, we propose a novel approach for training a convolutional multitask architecture with supervised learning and reinforcing it with weakly supervised learning. The architecture is simultaneously trained for three tasks: segmentation of red lesions and of bright lesions, those two tasks done concurrently with lesion detection. In addition, we propose and discuss the advantages of a new preprocessing method that guarantees the color consistency between the raw image and its enhanced version. Our complete system produces segmentations of both red and bright lesions.