Chapter 6 - Biomedical Visualization

Abstract

This chapter presents an overview of the techniques devised by scientific visualization research to address the specific needs of biomedical applications. Computers have become indispensable to the research and the clinical practice of biomedicine. Their widespread use now permits the manipulation of massive amounts of measured data, as well as, the study of sophisticated models through numerical simulations. The rapidly growing size and complexity of the resulting information from experiments or simulations creates a challenging demand on the tools and techniques needed to derive knowledge and insight from the data. Scientific visualization offers a very powerful approach to tackle this data analysis challenge by creating visual representations that convey salient properties of large data sets and permit their effective interpretation and analysis. The field of visualization is focused on creating images that convey salient information about underlying data and processes. In the past three decades, there has been unprecedented growth in computational and acquisition technologies, a growth that has resulted in an increased ability both to sense the physical world in precise detail and to model and simulate complex physical phenomena. As such, visualization plays a crucial role in our ability to comprehend such large and complex data—data which, in two, three, or more dimensions, convey insight into such diverse biomedical applications as understanding the bioelectric currents within the heart, characterizing white matter tracts by diffusion tensor imaging, and understanding morphology differences between different genetic mice phenotypes, among many others.