Machine learning and pattern classification in identification of indigenous retinal pathology

Herbert F. Jelinek; Anderson Rocha; Tiago Carvalho; Siome Goldenstein; Jacques Wainer

doi:10.1109/IEMBS.2011.6091471

Machine learning and pattern classification in identification of indigenous retinal pathology

Herbert F. Jelinek
, Anderson Rocha
, Tiago Carvalho
, Siome Goldenstein
, Jacques Wainer

Biomedical Engineering & Biotechnology

Universidade Estadual de Campinas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

26 Scopus citations

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.

Original language	British English
Title of host publication	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages	5951-5954
Number of pages	4
DOIs	https://doi.org/10.1109/IEMBS.2011.6091471
State	Published - 2011
Event	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States Duration: 30 Aug 2011 → 3 Sep 2011

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/Territory	United States
City	Boston, MA
Period	30/08/11 → 3/09/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1109/IEMBS.2011.6091471

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Jelinek, H. F., Rocha, A., Carvalho, T., Goldenstein, S., & Wainer, J. (2011). Machine learning and pattern classification in identification of indigenous retinal pathology. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 (pp. 5951-5954). Article 6091471 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/IEMBS.2011.6091471

Jelinek, Herbert F. ; Rocha, Anderson ; Carvalho, Tiago et al. / Machine learning and pattern classification in identification of indigenous retinal pathology. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. pp. 5951-5954 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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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.",

author = "Jelinek, \{Herbert F.\} and Anderson Rocha and Tiago Carvalho and Siome Goldenstein and Jacques Wainer",

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Jelinek, HF, Rocha, A, Carvalho, T, Goldenstein, S & Wainer, J 2011, Machine learning and pattern classification in identification of indigenous retinal pathology. in 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011., 6091471, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 5951-5954, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011, Boston, MA, United States, 30/08/11. https://doi.org/10.1109/IEMBS.2011.6091471

Machine learning and pattern classification in identification of indigenous retinal pathology. / Jelinek, Herbert F.; Rocha, Anderson; Carvalho, Tiago et al.
33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 5951-5954 6091471 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Jelinek HF, Rocha A, Carvalho T, Goldenstein S, Wainer J. Machine learning and pattern classification in identification of indigenous retinal pathology. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 5951-5954. 6091471. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/IEMBS.2011.6091471

Machine learning and pattern classification in identification of indigenous retinal pathology

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