Actas de congresos
Machine Learning And Pattern Classification In Identification Of Indigenous Retinal Pathology
Registro en:
9781424441211
Proceedings Of The Annual International Conference Of The Ieee Engineering In Medicine And Biology Society, Embs. , v. , n. , p. 5951 - 5954, 2011.
1557170X
10.1109/IEMBS.2011.6091471
2-s2.0-84055192129
Autor
Jelinek H.F.
Rocha A.
Carvalho T.
Goldenstein S.
Wainer J.
Institución
Resumen
Diabetic retinopathy (DR) is a complication of diabetes, which if untreated leads to blindness. DR early diagnosis and treatment improve outcomes. Automated assessment of single lesions associated with DR has been investigated for sometime. To improve on classification, especially across different ethnic groups, we present an approach using points-of-interest and visual dictionary that contains important features required to identify retinal pathology. Variation in images of the human retina with respect to differences in pigmentation and presence of diverse lesions can be analyzed without the necessity of preprocessing and utilizing different training sets to account for ethnic differences for instance. © 2011 IEEE.
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