Detection of Fundus Lesions Using Classifier Selection-Reference-Cited by-同舟云学术

Detection of Fundus Lesions Using Classifier Selection

Published:2009 Issue:5 Volume:E92-D Page:1168-1176
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

NAGAYOSHI Hiroto¹,HIRAMATSU Yoshitaka¹,SAKO Hiroshi¹,HIMAGA Mitsutoshi²,KATO Satoshi³

Affiliation:

1. Central Research Laboratory, Hitachi Ltd.

2. Hitachi-Omron Terminal Solutions, Corp.

3. Department of Ophthalmology, The University of Tokyo, School of Medicine

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://www.jstage.jst.go.jp/article/transinf/E92.D/5/E92.D_5_1168/_pdf

Reference18 articles.

1. [1] E. Stefánsson, “Prevention of diabetic blindness, ” British Journal of Ophthalmology, vol.90, pp.2-3, Jan. 2006.

2. [2] S. Yamamoto and H. Yokouchi, “Automatic diagnosis of color fundus photographs using TV camera system, ” The Journal of the Institute of Television Engineers of Japan, vol.29, pp.389-395, 1975.

3. [3] S. Lee, E. Lee, R. Kingsley, Y. Wang, D. Russell, R. Klein, and A. Warn, “Comparison of diagnosis of early retinal lesions of diabetic retinopathy between a computer system and human experts, ” Archives of Ophthalmology, vol.119, no.4, pp.509-515, 2001.

4. Hybrid fuzzy image processing for situation assessment [diabetic retinopathy]

5. [5] G. Luo, O. Chutatape, H. Li, and S. Krishnan, “Abnormality detection in automated mass screening system of diabetic retinopathy, ” 14th Symposium on Computer Based Medical Systems, pp.132-137, 2001.