Computer-Aided Diagnosis

Automatic nuclear cataract grading using image gradients

[+] Author Affiliations
Ruchir Srivastava

Institute for Infocomm Research, 138632 Singapore

Xinting Gao

Institute for Infocomm Research, 138632 Singapore

Fengshou Yin

Institute for Infocomm Research, 138632 Singapore

Damon W. K. Wong

Institute for Infocomm Research, 138632 Singapore

Jiang Liu

Institute for Infocomm Research, 138632 Singapore

Carol Y. Cheung

Singapore Eye Research Institute, Singapore 168751, Singapore

Tien Yin Wong

Singapore Eye Research Institute, Singapore 168751, Singapore

J. Med. Imag. 1(1), 014502 (Jun 04, 2014). doi:10.1117/1.JMI.1.1.014502
History: Received December 30, 2013; Revised March 12, 2014; Accepted May 9, 2014
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Abstract.  This paper deals with automatic grading of nuclear cataract (NC) from slit-lamp images in order to reduce the efforts in traditional manual grading. Existing works on this topic have mostly used brightness and color of the eye lens for the task but not the visibility of lens parts. The main contribution of this paper is in utilizing the visibility cue by proposing gray level image gradient-based features for automatic grading of NC. Gradients are important for the task because in a healthy eye, clear visibility of lens parts leads to distinct edges in the lens region, but these edges fade as severity of cataract increases. Experiments performed on a large dataset of over 5000 slit-lamp images reveal that the proposed features perform better than the state-of-the-art features in terms of both speed and accuracy. Moreover, fusion of the proposed features with the prior ones gives results better than any of the two used alone.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Ruchir Srivastava ; Xinting Gao ; Fengshou Yin ; Damon W. K. Wong ; Jiang Liu, et al.
"Automatic nuclear cataract grading using image gradients", J. Med. Imag. 1(1), 014502 (Jun 04, 2014). ; http://dx.doi.org/10.1117/1.JMI.1.1.014502


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