A survey of medical applications of 3D image analysis and computer graphics

3D gaze tracking system for NVidia 3D Vision®

Inappropriate parallax setting in stereoscopic content generally causes visual fatigue and visual discomfort. To optimize three dimensional (3D) effects in stereoscopic content by taking into account health issue, understanding how user gazes at 3D direction in virtual space is currently an important research topic. In this paper, we report the study of developing a novel 3D gaze tracking system for Nvidia 3D Vision(®) to be used in desktop stereoscopic display. We suggest an optimized geometric method to accurately measure the position of virtual 3D object. Our experimental result shows that the proposed system achieved better accuracy compared to conventional geometric method by average errors 0.83 cm, 0.87 cm, and 1.06 cm in X, Y, and Z dimensions, respectively.

A Web platform for the interactive visualization and analysis of the 3D fractal dimension of MRI data

This study presents a Web platform (http://3dfd.ujaen.es) for computing and analyzing the 3D fractal dimension (3DFD) from volumetric data in an efficient, visual and interactive way. The Web platform is specially designed for working with magnetic resonance images (MRIs) of the brain. The program estimates the 3DFD by calculating the 3D box-counting of the entire volume of the brain, and also of its 3D skeleton. All of this is done in a graphical, fast and optimized way by using novel technologies like CUDA and WebGL. The usefulness of the Web platform presented is demonstrated by its application in a case study where an analysis and characterization of groups of 3D MR images is performed for three neurodegenerative diseases: Multiple Sclerosis, Intrauterine Growth Restriction and Alzheimer's disease. To the best of our knowledge, this is the first Web platform that allows the users to calculate, visualize, analyze and compare the 3DFD from MRI images in the cloud.

Cancer Cell Image Analysis and Visualization

We review computerized cancer cell image analysis and visualization research over the past 30 years. Image acquisition, feature extraction, classification, and visualization from two-dimensional to three-dimensional image algorithms are introduced with case studies of bladder, prostate, breast, and renal carcinomas.