AUTOMATIC SEGMENTATION OF CAPILLARY NON-PERFUSION IN RETINAL ANGIOGRAMS

Amit Agarwal, Jayanthi Sivaswamy, Alka Rani, Taraprasad Das

2008

Abstract

Capillary Non-Perfusion (CNP) is a condition in diabetic retinopathy where blood ceases to flow to certain parts of the retina, potentially leading to blindness. This paper presents a solution for automatically detecting and segmenting CNP regions from fundus fluorescein angiograms (FFAs). CNPs are modelled as valleys, and a novel multiresolution technique for trough-based valley detection is presented. The proposed algorithm has been tested on 40 images and validated against expert-marked ground truth. Obtained results are presented as a receiver operating characteristic (ROC) curve. The area under this curve is 0.842 and the distance of ROC from the ideal point (0, 1) is 0.31.

Paper Citation

in Harvard Style

Agarwal A., Sivaswamy J., Rani A. and Das T. (2008). AUTOMATIC SEGMENTATION OF CAPILLARY NON-PERFUSION IN RETINAL ANGIOGRAMS . In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008) ISBN 978-989-8111-18-0, pages 170-177. DOI: 10.5220/0001058201700177

in Bibtex Style

@conference{biosignals08,
author={Amit Agarwal and Jayanthi Sivaswamy and Alka Rani and Taraprasad Das},
title={AUTOMATIC SEGMENTATION OF CAPILLARY NON-PERFUSION IN RETINAL ANGIOGRAMS},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)},
year={2008},
pages={170-177},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001058201700177},
isbn={978-989-8111-18-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)
TI - AUTOMATIC SEGMENTATION OF CAPILLARY NON-PERFUSION IN RETINAL ANGIOGRAMS
SN - 978-989-8111-18-0
AU - Agarwal A.
AU - Sivaswamy J.
AU - Rani A.
AU - Das T.
PY - 2008
SP - 170
EP - 177
DO - 10.5220/0001058201700177