Detection of Fundus Lesions Using Classifier Selection

Hiroto NAGAYOSHI  Yoshitaka HIRAMATSU  Hiroshi SAKO  Mitsutoshi HIMAGA  Satoshi KATO  

IEICE TRANSACTIONS on Information and Systems   Vol.E92-D    No.5    pp.1168-1176
Publication Date: 2009/05/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E92.D.1168
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Biological Engineering
fundus,  diabetic retinopathy,  CAD,  image processing,  image normalization,  classifier,  

Full Text: PDF(1.4MB)>>
Buy this Article

A system for detecting fundus lesions caused by diabetic retinopathy from fundus images is being developed. The system can screen the images in advance in order to reduce the inspection workload on doctors. One of the difficulties that must be addressed in completing this system is how to remove false positives (which tend to arise near blood vessels) without decreasing the detection rate of lesions in other areas. To overcome this difficulty, we developed classifier selection according to the position of a candidate lesion, and we introduced new features that can distinguish true lesions from false positives. A system incorporating classifier selection and these new features was tested in experiments using 55 fundus images with some lesions and 223 images without lesions. The results of the experiments confirm the effectiveness of the proposed system, namely, degrees of sensitivity and specificity of 98% and 81%, respectively.

open access publishing via