Joo Hwee Lim

Learn More
Glaucoma is a leading cause of permanent blindness. However, disease progression can be limited if detected early. The optic cup-to-disc ratio (CDR) is one of the main clinical indicators of glaucoma, and is currently determined manually, limiting its potential in mass screening. In this paper, we propose an automatic CDR determination method using a(More)
Glaucoma is a leading cause of permanent blindness. ARGALI, an automated system for glaucoma detection, employs several methods for segmenting the optic cup and disc from retinal images, combined using a fusion network, to determine the cup to disc ratio (CDR), an important clinical indicator of glaucoma. This paper discusses the use of SVM as an(More)
An automatic approach to detect cortical opacities and grade the severity of cortical cataract from retro-illumination images is proposed. The spoke-like feature of cortical opacity is employed to separate from other opacity type. The proposed algorithms were tested by images from a community study. The success rate of region of interest (ROI) detection is(More)
This paper presents a novel multi-level approach for bleeding detection in Wireless Capsule Endoscopy (WCE) images. In the low-level processing, each cell of K×K pixels is characterized by an adaptive color histogram which optimizes the information representation for WCE images. A Neural Network (NN) cell-classifier is trained to classify cells in an(More)
Species diversity in mixed forest stands is one of the factors that complicate up-scaling of transpiration from individual trees to stand level, since tree species are architecturally and functionally different. In this study, thermal dissipation probes were used to measure sap flow in five different tree species in a mixed-deciduous mountain forest in(More)
Cataract is one of the leading causes of blindness worldwide. A computer-aided approach to assess nuclear cataract automatically and objectively is proposed in this paper. An enhanced Active Shape Model (ASM) is investigated to extract robust lens contour from slit-lamp images. The mean intensity in the lens area, the color information on the central(More)
Cataract remains a leading cause for blindness worldwide. Cataract diagnosis via human grading is subjective and time-consuming. Several methods of automatic grading are currently available, but each of them suffers from some drawbacks. In this paper, a new approach for automatic detection based on texture and intensity analysis is proposed to address the(More)
PURPOSE To validate a new computer-aided diagnosis (CAD) imaging program for the assessment of nuclear lens opacity. METHODS Slit-lamp lens photographs from the Singapore Malay Eye Study (SiMES) were graded using both the CAD imaging program and manual assessment method by a trained grader using the Wisconsin Cataract Grading System. Cataract was(More)
Nonlinear support vector machines (SVMs) rely on the kernel trick and tradeoff parameters to build nonlinear models to classify complex problems and balance misclassification and generalization. The inconvenience in determining the kernel and the parameters has motivated the use of local nearest neighbor (NN) classifiers in lieu of global classifiers. This(More)