NDLI: Comparison of classifier performance for information fusion in automated Diabetic Retinopathy screening

Content Provider	IEEE Xplore Digital Library
Author	Niemeijer, M. Abramoff, M.D. Joshi, N. Brady, M.
Copyright Year	2011
Description	Author affiliation: The University of Iowa, Department of Ophthalmology and Visual Sciences, Department of Electrical and Computer Engineering, USA (Niemeijer, M.; Abramoff, M.D.) \|\| Wolfson Medical Vision Lab, University of Oxford, U.K. (Joshi, N.; Brady, M.)
Abstract	Diabetic Retinopathy (DR) is a vascular disorder affecting the retina due to prolonged Diabetes. It can lead to sudden vision loss in advanced stages. Screening and routine monitoring is the most effective way of avoiding vision loss due to DR. Abramoff et al.[1] developed and evaluated an automated DR screening system. One of the most important parts of this system, the information fusion module, combines information obtained from different images and various image properties. Niemeijer et al. [2] compared several methods for DR information fusion and concluded that k-Nearest Neighbour (kNN) provided the best performance for their system. The aim of this work was to compare performance of the Random Forest (RF) classifier with that of the kNN classifier for DR information fusion. We performed experiments on a dataset containing images from 10303 eye examinations. Additionally we also compared performance of the two classifiers in an important sub-problem of DR screening - red lesion detection. In both the experiments, the RF classifier showed significantly better performance.
Starting Page	685
Ending Page	688
File Size	147924
Page Count	4
File Format	PDF
ISBN	9781424441273
ISSN	19457928
DOI	10.1109/ISBI.2011.5872499
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radio frequency Diabetes Lesions Training Retinopathy Vegetation Sensitivity kNN Diabetic Retinopathy CAD information fusion Random Forest
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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