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A Computer Assisted Method for Nuclear Cataract Grading From Slit-Lamp Images Using Ranking

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6 Author(s)
Wei Huang ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore ; Kap Luk Chan ; Huiqi Li ; Joo Hwee Lim
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In clinical diagnosis, a grade indicating the severity of nuclear cataract is often manually assigned by a trained ophthalmologist to a patient after comparing the lens' opacity severity in his/her slit-lamp images with a set of standard photos. This grading scheme is often subjective and time-consuming. In this paper, a novel computer-aided diagnosis method via ranking is proposed to facilitate nuclear cataract grading following conventional clinical decision-making process. The grade of nuclear cataract in a slit-lamp image is predicted using its neighboring labeled images in a ranked image list, which is achieved using a learned ranking function. This ranking function is learned via direct optimization on a newly proposed approximation to a ranking evaluation measure. Our proposed method has been evaluated by a large dataset composed of 1000 different cases, which are collected from an ongoing clinical population-based study. Both experimental results and comparison with several existing methods demonstrate the benefit of grading via ranking by our proposed method.

Published in:

Medical Imaging, IEEE Transactions on  (Volume:30 ,  Issue: 1 )

Date of Publication:

Jan. 2011

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