Automatic retina exudates segmentation without a manually labelled training set

L. Giancardo, F. Meriaudeau, T. P. Karnowski, Y. Li, K. W. Tobin, Edward Chaum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

42 Citations (Scopus)

Abstract

Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy which can be assessed by detecting exudates (a type of bright lesion) in fundus images. In this work, two new methods for the detection of exudates are presented which do not use a supervised learning step; therefore, they do not require labelled lesion training sets which are time consuming to create, difficult to obtain and prone to human error. We introduce a new dataset of fundus images from various ethnic groups and levels of DME which we have made publicly available. We evaluate our algorithm with this dataset and compare our results with two recent exudate segmentation algorithms. In all of our tests, our algorithms perform better or comparable with an order of magnitude reduction in computational time.

Original languageEnglish (US)
Title of host publication2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI'11
Pages1396-1400
Number of pages5
DOIs
StatePublished - Nov 2 2011
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: Mar 30 2011Apr 2 2011

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
CountryUnited States
CityChicago, IL
Period3/30/114/2/11

Fingerprint

Exudates and Transudates
Retina
Macular Edema
Supervised learning
Diabetic Retinopathy
Ethnic Groups
Learning
Datasets

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Giancardo, L., Meriaudeau, F., Karnowski, T. P., Li, Y., Tobin, K. W., & Chaum, E. (2011). Automatic retina exudates segmentation without a manually labelled training set. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 (pp. 1396-1400). [5872661] (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2011.5872661

Automatic retina exudates segmentation without a manually labelled training set. / Giancardo, L.; Meriaudeau, F.; Karnowski, T. P.; Li, Y.; Tobin, K. W.; Chaum, Edward.

2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. p. 1396-1400 5872661 (Proceedings - International Symposium on Biomedical Imaging).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Giancardo, L, Meriaudeau, F, Karnowski, TP, Li, Y, Tobin, KW & Chaum, E 2011, Automatic retina exudates segmentation without a manually labelled training set. in 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11., 5872661, Proceedings - International Symposium on Biomedical Imaging, pp. 1396-1400, 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11, Chicago, IL, United States, 3/30/11. https://doi.org/10.1109/ISBI.2011.5872661
Giancardo L, Meriaudeau F, Karnowski TP, Li Y, Tobin KW, Chaum E. Automatic retina exudates segmentation without a manually labelled training set. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. p. 1396-1400. 5872661. (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2011.5872661
Giancardo, L. ; Meriaudeau, F. ; Karnowski, T. P. ; Li, Y. ; Tobin, K. W. ; Chaum, Edward. / Automatic retina exudates segmentation without a manually labelled training set. 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. pp. 1396-1400 (Proceedings - International Symposium on Biomedical Imaging).
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