Medical image processing, analysis & visualization in clinical research

Abstract

Imaging has become an essential component in many fields of medical and laboratory research and clinical practice. Biologists study cells and generate 3D confocal microscopy datasets, virologists generate 3D reconstructions of viruses from micrographs, radiologists identify and quantify tumors from MRI and CT scans, and neuroscientists detect regional metabolic brain activity from PET and functional MRI scans. Analysis of these diverse image types requires sophisticated computerized quantification and visualization tools. Until recently, three-dimensional visualization of images and quantitative analysis could only be performed using expensive UNIX workstations and customized software. Today, much of the visualization and analysis can be performed on an inexpensive desktop computer equipped with the appropriate graphics hardware and software. This paper introduces an extensible platform-independent, general-purpose image processing and visualization program specifically designed to meet the needs of a In ternet-linked medical research community. The application named MIPAV (Medical Image Processing Analysis and Visualization) enables clinical and quantitative analysis of medical images over the Internet. Using MIPAV's standard user-interface and analysis tools, researchers and clinicians at remote sites can easily share research data and analyses, thereby enhancing their ability to study, diagnose, monitor, and treat medical disorders.