Abstract
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.
Highlights
Retinopathy of Prematurity (ROP) is a progressive disorder that affects premature infants of very low birth weight (
We focus our efforts on building a system to assist diagnosis of only Aggressive Posterior ROP (APROP), without the cooccurrence of other retinal pathologies
Since we study aggressive posterior retinopathy, our focus is on the vessel activity close to the optic disc (OD) which is predominantly in DR1 and extended DR1 (EDR1)
Summary
Retinopathy of Prematurity (ROP) is a progressive disorder that affects premature infants of very low birth weight (
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