A computer assisted method for nuclear cataract grading from slit-lamp images using ranking.
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.
Huang
Wei
W
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. n060101@ntu.edu.sg
Chan
Kap Luk
KL
Li
Huiqi
H
Lim
Joo Hwee
JH
Liu
Jiang
J
Wong
Tien Yin
TY
D002386:Cataract / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003952:Diagnostic Imaging / Q000379:methods*; D003941:Diagnostic Techniques, Ophthalmological; D006801:Humans; D007907:Lens Nucleus, Crystalline / Q000473:pathology; D010781:Photography / Q000379:methods; D010808:Physical Examination / Q000295:instrumentation / Q000379:methods; D012107:Research Design; D018709:Statistics, Nonparametric