A novel hybrid approach for automated detection of retinal detachment using ultrasound images

Joel En Wei Koh; U Raghavendra; Anjan Gudigar; Ooi Chui Ping; Filippo Molinari; Samarth Mishra; Sinnakaruppan Mathavan; Rajiv Raman; U Rajendra Acharya

doi:10.1016/j.compbiomed.2020.103704

A novel hybrid approach for automated detection of retinal detachment using ultrasound images

Comput Biol Med. 2020 May:120:103704. doi: 10.1016/j.compbiomed.2020.103704. Epub 2020 Mar 19.

Authors

Joel En Wei Koh¹, U Raghavendra², Anjan Gudigar², Ooi Chui Ping³, Filippo Molinari⁴, Samarth Mishra⁵, Sinnakaruppan Mathavan⁵, Rajiv Raman⁵, U Rajendra Acharya⁶

Affiliations

¹ Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi, 599489, Singapore.
² Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
³ School of Science and Technology, Singapore University of Social Sciences, 463 Clementi Road, 599494, Singapore.
⁴ Department of Electronics and Telecommunications, Politecnico di Torino, Italy.
⁵ ONGC Department of Genetics and Molecular Biology, Vision Research Foundation, Sankarnethralaya campus, Chennai, 600006, India.
⁶ Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi, 599489, Singapore; Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan; International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto, Japan. Electronic address: aru@np.edu.sg.

PMID: 32250849
DOI: 10.1016/j.compbiomed.2020.103704

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.

Keywords: Classifier; Cumulant; HOS; Image; Retinal detachment; Texture; Ultrasound.

MeSH terms

Emergency Service, Hospital
Humans
Retina
Retinal Detachment* / diagnostic imaging
Ultrasonography
Vitreous Detachment*