CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Filtering video volumes using the graphics hardware
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Vessel segmentation for ablation treatment planning and simulation
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Illustrative Couinaud segmentation for ultrasound liver examinations
SG'11 Proceedings of the 11th international conference on Smart graphics
Evaluation of diffusion filters for 3d CTA liver vessel enhancement
MICCAI'12 Proceedings of the 4th international conference on Abdominal Imaging: computational and clinical applications
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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.