Visualization and labeling of the Visible Human^™ dataset: Challenges & resolves

Abstract

The Visible Human^™ is a vast resource, which few methods can fully explore and analyze. We aim to completely label and volume display it; here we discuss the main obstacles, and our means for overcoming them. Our segmentation into over 350 anatomical regions spans the various body systems. Volume rendering by a memory-independent, partitioned, color and translucency scheme gives realistic human images, with many possibilities for medical education and “edutainment”.

The authors thank Tim Poston and Raghu Raghavan for their valuable technical and editorial comments. We are grateful to Ms. Jin Xiaoyang and all the NUS students who enthusiastically segmented the data with great patience and precision. We also express our gratitude to Chun Pong Yu and Pingli Pang who developed the keyframe animation, and built and integrated the GUI for the rendering system. Thanks to Seema Mullick for her support in segmenting data and in matters related to design aesthetics. This work would not have been possible without the support of the National Institutes of Health for the Visible Human Project.