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Red lesion detection using dynamic shape features for diabetic retinopathy screening

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1109/TMI.2015.2509785
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FormatText, Article
Subjectscreening; computer aided diagnostic; diabetic retinopathy; fundus IMAGING; lesion detection; retina
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.
Publication date
PublisherInstitute of Electrical and Electronics Engineers
In
  • IEEE Transactions on Medical Imaging 35, no. 4: 1116–1126.
LanguageEnglish
Peer reviewedYes
NRC publication
This is a non-NRC publication

"Non-NRC publications" are publications authored by NRC employees prior to their employment by NRC.

NPARC number23000991
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Record identifier94843b2f-f661-4da7-a120-8d560211a5f5
Record created2016-11-25
Record modified2020-03-16
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