We describe a software system for building three-dimensional (3D) models from colonoscopic videos. The system is end-to-end in the sense that it takes as input raw image frames—shot during a colon exam—and produces the 3D structure of objects of interest (OOI), such as tumors, polyps, and lesions. We use the structure-from-motion (SfM) approach in computer vision which analyzes an image sequenc...

Diabetic retinopathy (DR) has become one of the major causes blindness. Due to increased prevalence diabetes worldwide, diabetic patients exhibit high probabilities developing DR. There is a need develop labor-less computer-aided diagnosis system support clinical diagnosis. Here, we attempted simple methods for severity grading and lesion detection from retinal fundus images. We developed DR by...

Universal Lesion Detection (ULD) in computed tomography plays an essential role computer-aided diagnosis. Promising ULD results have been reported by multi-slice-input detection approaches which model 3D context from multiple adjacent CT slices, but such methods still experience difficulty obtaining a global representation among different slices and within each individual slice since they only ...

Computer methodologies are being developed to assist radiologists, as second readers, in the interpretation of mammograms. This could represent further amelioration by increasing diagnostic accuracy in the screening programs. We have developed a computerized scheme to detect clustered microcalcifications in digital mammograms, using 100 mammograms that were randomly selected from the mammograph...

Computer-aided diagnosis techniques in medical imaging are developed for the automated differentiation between benign and malignant lesions and go beyond computer-aided detection by providing cancer likelihood for a detected lesion given image and/or patient characteristics. The goal of this study was the development and evaluation of a computer-aided detection and diagnosis algorithm for mammo...

Universal Lesion Detection (ULD) in computed tomography plays an essential role computer-aided diagnosis. Promising ULD results have been reported by coarse-to-fine two-stage detection approaches, but such methods still suffer from issues like imbalance of positive v.s. negative anchors during object proposal and insufficient supervision problem localization regression classification the region...