A novel hybrid approach for automated detection of retinal detachment using ultrasound images. (May 2020)

• Record Type: Journal Article
• Authors: Koh, Joel En Wei; Raghavendra, U.; Gudigar, Anjan; Ping, Ooi Chui; Molinari, Filippo; Mishra, Samarth; Mathavan, Sinnakaruppan; Raman, Rajiv; Acharya, U.Rajendra
• Is Part Of: Computers in biology and medicine. Volume 120(2020)
• Publication Date: 2020-05
• Subjects: Retinal detachment -- Texture -- Ultrasound -- Classifier -- Image -- HOS -- Cumulant; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2020.103704
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Retinal detachment (RD) is an ocular emergency, which needs quick intervention to preclude permanent vision loss. In general, ocular ultrasound is used by ophthalmologists to enhance their judgment in detecting RD in eyes with media opacities which precludes the retinal evaluation. However, the quality of ultrasound (US) images may be degraded due to the presence of noise, and other retinal conditions may cause membranous echoes. All these can influence the accuracy of diagnosis. Hence, to overcome the above, we are proposing an automated system to detect RD using texton, higher order spectral (HOS) cumulants and locality sensitive discriminant analysis (LSDA) techniques. Our developed method is able to classify the posterior vitreous detachment and RD using support vector machine classifier with highest accuracy of 99.13%. Our system is ready to be tested with more diverse ultrasound images and aid ophthalmologists to arrive at a more accurate diagnosis. Graphical abstract: Image 1 Highlights: Automated detection of retinal detachment using US images. Textons, HOS cumulants and LSDA techniques are considered. Obtained classification accuracy of 99.13% using SVM classifier. System can aid ophthalmologists to arrive at accurate diagnosis.