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|Type:||Artigo de evento|
|Title:||Machine Learning And Pattern Classification In Identification Of Indigenous Retinal Pathology|
|Abstract:||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.|
|Citation:||Proceedings Of The Annual International Conference Of The Ieee Engineering In Medicine And Biology Society, Embs. , v. , n. , p. 5951 - 5954, 2011.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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