Author/Editor		Klemenčič, J; Valenčič, Vojko; Bošnjak, Roman; Jurčič-Zlobec, Borut; Šuc, Edi
Title		Using the visible human data set for segmentation and tumor removal surgery planning
Type		članek
Source		In: Arabnia HR, editor. CISST'99. Proceedings of the international conference on imaging science, systems, and technology; 1999 Jun 28-Jul 1; Las Vegas, Nevada, USA. Las Vegas: CSREA Press,
Publication year		1999
Language		eng
Abstract		The MR, CT and anatomical cross-section image data sets, acquired through the Visible Human Project, represent a common reference in various research fields such as the study of human anatomy, treatment planning, modeling in numerical dozimetry and for virtual reality applications in medicine. The usefulness of the sets is much improved by segmenting the raw image data and linking it to text-based data, thus creating a 3D anatomical atlas. The segmented sets can be used as a deformable atlas for automatic segmentation of patient specific CT or MR images. This is achieved by deforming the atlas model into the patient model, and linking the text-based data from atlas to patient images. Such a deformation is based on mathematical modelling of linear elastic and viscous fluid materials and is very efficient, but computationally expensive. To simpify it, the volume deformation can be exchanged for 3D surface model matching. An effective algorithm, resulting in 3D model of selected organs/tissues can significantly improve CT or MR scan based diagnostics. We demonstrate how to create a segmented, patient specific 3D model of the brain with a tumor, which can be interactively used by the surgeon for more efficient tumor removal surgery planning.
Descriptors		ANATOMY, CROSS-SECTIONAL MAGNETIC RESONANCE IMAGING TOMOGRAPHY, X-RAY COMPUTED BRAIN NEOPLASMS DIAGNOSIS, COMPUTER-ASSISTED COMPUTER SIMULATION