Computer-aided diagnosis of plus disease via measurement of vessel thickness in retinal fundus images of preterm infants

Changes in the characteristics of retinal vessels such as width and tortuosity can be signs of the presence of several diseases such retinopathy of prematurity (ROP) and diabetic retinopathy. Plus disease is an indicator of ROP which requires treatment and is signified by an increase in posterior venular width. In this work, we present image processing techniques for the detection, segmentation, tracking, and measurement of the width of the major temporal arcade (MTA), which is the thickest venular branch in the retina. Several image processing techniques have been employed, including the use of Gabor filters to detect the MTA, morphological image processing to obtain its skeleton, Canny׳s method to detect and select MTA vessel-edge candidates, least-squares fitting to interpolate the MTA edges, and geometrical procedures to measure the width of the MTA. The results, obtained using 110 retinal fundus images of preterm infants, indicate a statistically highly significant difference in MTA width of normal cases as compared to cases with plus disease (p<0.01). The results provide good accuracy in computer-aided diagnosis (CAD) of plus disease with an area under the receiver operating characteristic curve of 0.76. The proposed methods may be used in CAD of plus disease and timely treatment of ROP in a clinical or teleophthalmological setting.