Paper Info
Title
Automated detection of retinal whitening in malarial retinopathy.
Abstract
Cerebral malaria (CM) is a severe neurological complication associated with malarial infection. Malaria affects approximately 200 million people worldwide, and claims 600,000 lives annually, 75% of whom are African children under five years of age. Because most of these mortalities are caused by the high incidence of CM misdiagnosis, there is a need for an accurate diagnostic to confirm the presence of CM. The retinal lesions associated with malarial retinopathy (MR) such as retinal whitening, vessel discoloration, and hemorrhages, are highly specific to CM, and their detection can improve the accuracy of CM diagnosis. This paper will focus on development of an automated method for the detection of retinal whitening which is a unique sign of MR that manifests due to retinal ischemia resulting from CM. We propose to detect the whitening region in retinal color images based on multiple color and textural features. First, we preprocess the image using color and textural features of the CMYK and CIE-XYZ color spaces to minimize camera reflex. Next, we utilize color features of the HSL, CMYK, and CIE-XYZ channels, along with the structural features of difference of Gaussians. A watershed segmentation algorithm is used to assign each image region a probability of being inside the whitening, based on extracted features. The algorithm was applied to a dataset of 54 images (40 with whitening and 14 controls) that resulted in an image-based (binary) classification with an AUC of 0.80. This provides 88% sensitivity at a specificity of 65%. For a clinical application that requires a high specificity setting, the algorithm can be tuned to a specificity of 89% at a sensitivity of 82%. This is the first published method for retinal whitening detection and combining it with the detection methods for vessel discoloration and hemorrhages can further improve the detection accuracy for malarial retinopathy.
Year
DOI
Venue
2016
10.1117/12.2217188
Proceedings of SPIE
Keywords
Field
DocType
malarial retinopathy,cerebral malaria,retinal whitening,retina,computer-aided diagnosis
Computer vision,Retinopathy,Color space,Retina,Computer-aided diagnosis,Optics,Image segmentation,RGB color model,Artificial intelligence,Retinal,Difference of Gaussians,Physics
Conference
Volume
ISSN
Citations 
9785
0277-786X
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
Vinayak S. Joshi1163.96
Carla Agurto2858.22
E. Simon Barriga3417.98
Sheila C. Nemeth42210.10
Peter Soliz510425.51
I. MacCormick600.68
Terrie E. Taylor711.75
S. Lewallen801.01
S. Harding900.68