Red Lesion Detection Using Dynamic Shape Features for Diabetic Retinopathy Screening.

Abstract:

:The development of an automatic telemedicine system for computer-aided screening and grading of diabetic retinopathy depends on reliable detection of retinal lesions in fundus images. In this paper, a novel method for automatic detection of both microaneurysms and hemorrhages in color fundus images is described and validated. The main contribution is a new set of shape features, called Dynamic Shape Features, that do not require precise segmentation of the regions to be classified. These features represent the evolution of the shape during image flooding and allow to discriminate between lesions and vessel segments. The method is validated per-lesion and per-image using six databases, four of which are publicly available. It proves to be robust with respect to variability in image resolution, quality and acquisition system. On the Retinopathy Online Challenge's database, the method achieves a FROC score of 0.420 which ranks it fourth. On the Messidor database, when detecting images with diabetic retinopathy, the proposed method achieves an area under the ROC curve of 0.899, comparable to the score of human experts, and it outperforms state-of-the-art approaches.

journal_name

IEEE Trans Med Imaging

authors

Seoud L,Hurtut T,Chelbi J,Cheriet F,Langlois JM

doi

10.1109/TMI.2015.2509785

subject

Has Abstract

pub_date

2016-04-01 00:00:00

pages

1116-26

issue

4

eissn

0278-0062

issn

1558-254X

journal_volume

35

pub_type

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