Automatic detection of microaneurysms and haemorrhages in fundus images using dynamic shape features

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TypeArticle
Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, 29 April-2May, 2014, Beijing, China
Subjectimage processing; features extraction; computer aided detection; fundus images
AbstractThis paper presents a novel approach for automatic detection of microaneurysms and haemorrhages in fundus images. First, it begins with a preprocessing stage for shade correction, contrast enhancement and denoising. Second, all regional minima with sufficient contrast are extracted and considered as candidates. Third, in an image flooding scheme, a new set of dynamic shape features is computed as a function of intensity. Finally, a Random Forest classifies the candidates into lesions and non lesions. A set of 143 fundus images with an average of 2210 pixels in diameter was acquired using different cameras and used for training and testing. The proposed approach achieved a global score over the FROC curve of 0.393, while previous work with images of similar resolution reported a score of 0.233.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada
Peer reviewedYes
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This is a non-NRC publication

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

NPARC number23001007
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Record identifier8d7b88f8-5f56-4f19-b277-fbf8d436a97a
Record created2016-11-28
Record modified2016-11-28
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