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An Efficient and Clinical-Oriented 3D Liver Segmentation Method

delete2017-01-01
delete14
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OA
AI
Q
Qin Zhang
Y
Yingfang Fan *
J
Jiafu Wan
刘艳霞 (Yanxia Liu) *
DOI:10.1109/ACCESS.2017.2754298delete
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Abstract

Abstract

En 中文
By segmenting, modeling, and visualizing computed tomography sequence data, surgeons can better understand the spatial relationship of the intrahepatic vein, portal vein, artery, and tumor. Accurate preoperative understanding of liver anatomy and volume of the corresponding liver segment are necessary for anatomical liver resection. This paper gives an efficient and semiautomatic method for segmenting the liver in clinical cases. This method is based on Couinauds theory and automatically divides the liver segment by portal vein branches. Considering the vascular variation of individual cases, the adjustment of the portal vein branches was provided on the basis of automatic segmentation, thus adaptability to various cases was implemented. For the final segmentation results, the portal vein blood supply of different liver segments can be confirmed by 3-D visualization, and the liver volume can be accurately estimated. Experiments show that this liver segmentation method has good clinical value.
Keywords:
Liver anatomy
CT image segmentation and reconstruction
3D Visualization
Couinaud's segments
vascular tree of portal vein
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Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

S
southern medical university - china
Scholars:
4.6W
Papers: 2.5W
Citations: 50
S
south china university of technology
Scholars:
6.7W
Papers: 5.1W
Citations: 85