Automatic Hepatic Vessel Segmentation Using Graphics Hardware

Marius Erdt, Matthias Raspe, Michael Suehling
Fraunhofer Institute for Computer Graphics, Cognitive Computing & Medical Imaging, Fraunhoferstrasse 5, 64283 Darmstadt, Germany
Medical Imaging and Augmented Reality, Lecture Notes in Computer Science, 2008, Volume 5128/2008, 403-412


   title={Automatic hepatic vessel segmentation using graphics hardware},

   author={Erdt, M. and Raspe, M. and Suehling, M.},

   journal={Medical Imaging and Augmented Reality},





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The accurate segmentation of liver vessels is an important prerequisite for creating oncologic surgery planning tools as well as medical visualization applications. In this paper, a fully automatic approach is presented to quickly enhance and extract the vascular system of the liver from CT datasets. Our framework consists of three basic modules: vessel enhancement on the graphics processing unit (GPU), automatic vessel segmentation in the enhanced images and an option to verify and refine the obtained results. Tests on 20 clinical datasets of varying contrast quality and acquisition phase were carried out to evaluate the robustness of the automatic segmentation. In addition the presented GPU based method was tested against a CPU implementation to demonstrate the performance gain of using modern graphics hardware. Automatic segmentation using graphics hardware allows reliable and fast extraction of the hepatic vascular system and therefore has the potential to save time for oncologic surgery planning.
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