Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity

被引:18
|
作者
Rajashekar, Deepthi [1 ,4 ]
Srinivasa, Gowri [1 ,2 ]
Vinekar, Anand [3 ]
机构
[1] PESIT, PES Ctr Pattern Recognit, Bangalore South Campus, Bengaluru, Karnataka, India
[2] PESIT, Dept Comp Sci & Engn, Bangalore South Campus, Bengaluru, Karnataka, India
[3] Narayana Nethralaya Post Grad Inst Ophthalmol, Dept Pediat Retina, Bengaluru, Karnataka, India
[4] Dalhousie Univ, Fac Comp Sci, Halifax, NS, Canada
来源
PLOS ONE | 2016年 / 11卷 / 10期
关键词
TELE-MEDICINE; PLUS DISEASE; INDIA; DIAGNOSIS;
D O I
10.1371/journal.pone.0163923
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Computer aided analysis plays a nontrivial role in assisting the diagnosis of various eye pathologies. In this paper, we propose a framework to help diagnose the presence of Aggressive Posterior Retinopathy Of Prematurity (APROP), a pathology that is characterised by rapid onset and increased tortuosity of blood vessels close to the optic disc (OD). We quantify vessel characteristics that are of clinical relevance to APROP such as tortuosity and the extent of branching i.e., vessel segment count in the defined diagnostic region. We have adapted three vessel segmentation techniques: matched filter response, scale space theory and morphology with local entropy based thresholding. The proposed feature set equips us to build a linear discriminant classifier to discriminate APROP images from clinically healthy images. We have studied 36 images from 21 APROP subjects against a control group of 15 clinically healthy age matched infants. All subjects are age matched ranging from 33-40 weeks of post menstrual age. Experimental results show that we attain 100% recall and 95.45% precision, when the vessel network obtained from morphology is used for feature extraction.
引用
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页数:17
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