Yongming Xie BS, Abstract Co-Author: Nothing to Disclose

Xinghe Wang BS, Abstract Co-Author: Nothing to Disclose

Guangyu Wang, Abstract Co-Author: Nothing to Disclose

Simon Sze Ming Ho MBBS, Abstract Co-Author: RGC grant, CUHK4461/05M

Pheng Ann Heng PhD, Presenter: Nothing to Disclose

Virtual anatomy is one of the advanced techniques which can shorten the process on learning different human anatomical structures. Liver is one of the most important and complex human organs. Deploying the high-resolution Chinese Visible Human (CVH) dataset and advanced visualization technologies, we have developed a powerful virtual liver environment for visualizing fine detailed anatomical structures on PC platform.

The liver region in CVH dataset has been segmented into several important parts, including: left and right lobes of liver, common hepatic duct, common hepatic v., hepatic portal v., gallbladder, common bile duct, and so on. Various liver tissues can be visualized individually. Based on the OpenGL and DirectX techniques, we reconstruct the 3D volume from the 2D slices. Most time-consuming computations are carried out on graphics processing units (GPU).

The user interface provides fully interactive navigation controls, including zoom in/out, multiple cutting-plan dissections, travel, and so on. Students can examine various liver-anatomical structures with extremely fine details and photorealistic rendering. Users can freely assign pseudo-color to label different tissues.

Through the advanced virtual reality and visualization techniques, the proposed virtual liver environment has been developed as a powerful tool for efficient learning of liver-anatomical structures on PC platform. This system can be further exploited as a surgery simulator of liver and gallbladder.

Our elegant virtual environment provides fine-detailed visualization of liver anatomy. It will help students to understand liver region, which is one of the most important and complex ones.

Xie, Y, Wang, X, Wang, G, Ho, S, Heng, P, Virtual Liver Environment Based on Chinese Visible Human Data.  Radiological Society of North America 2007 Scientific Assembly and Annual Meeting, November 25 - November 30, 2007 ,Chicago IL. http://archive.rsna.org/2007/5013484.html