Red lesions detection in digital fundus images

Author

Balasubramanian, S. ; Pradhan, Sandip ; Chandrasekaran, V.

Author_Institution

Dept. of Math. & Comput. Sci., Sri Sathya Sai Univ., Puttaparthi

fYear

2008

fDate

12-15 Oct. 2008

Firstpage

2932

Lastpage

2935

Abstract

In this paper we propose a novel method for automatic detection red lesions in digital fundus images. Candidate red lesions are extracted by a novel method called automatic seed generation (ASG). For classification, an implicitly hybrid classifier called spatio temporal feature map classifier (STFM) has been employed. Inclusion of a new feature called elliptic variance during classification phase has significantly reduced the false positives. The hybrid classifier reports 87% sensitivity and 95.53% specificity.

Keywords

diseases; eye; feature extraction; image classification; medical image processing; automatic seed generation; digital fundus image; elliptic variance; feature extraction; red lesions detection; spatio temporal feature map classifier; Biomedical imaging; Blood vessels; Computer science; Diabetes; Image analysis; Image databases; Lesions; Mathematics; Retina; Spatial databases; Automatic Seed Generation; Elliptic Variance; Microaneurysm; Retinal image analysis; STFM;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1522-4880

Print_ISBN

978-1-4244-1765-0

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2008.4712409

Filename

4712409