title: A computer-aided diagnosis system of nuclear cataract via ranking.
abstract: A novel computer-aided diagnosis system of nuclear cataract via ranking is firstly proposed in this paper. The grade of nuclear cataract in a slit-lamp image is predicted based on its neighboring labeled images in a ranked images list, which is achieved using an optimal ranking function. A new ranking evaluation measure is proposed for learning the optimal ranking function via direct optimization. Our system has been tested by a large dataset composed of 1000 slit-lamp images from 1000 different cases. Both experimental results and comparison with several state-of-the-art methods indicate the superiority of our system.
authors.affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
authors.forename: Wei
authors.initials: W
authors.lastname: Huang
authors.forename: Huiqi
authors.initials: H
authors.lastname: Li
authors.forename: Kap Luk
authors.initials: KL
authors.lastname: Chan
authors.forename: Joo Hwee
authors.initials: JH
authors.lastname: Lim
authors.forename: Jiang
authors.initials: J
authors.lastname: Liu
authors.forename: Tien Yin
authors.initials: TY
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002386:Cataract / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009887:Ophthalmoscopy / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity