Please use this identifier to cite or link to this item: https://doi.org/10.1109/BMEI.2010.5639989
Title: Segmentation of gallbladder from CT images for a surgical training system
Authors: Zhou, J.
Huang, W.
Zhang, J.
Yang, T.
Liu, J.
Chui, C.K. 
Chang, S.
Keywords: Gallbladder
Image segmentation
Image-guided surgical training
Support vector machine (SVM)
Issue Date: 2010
Source: Zhou, J., Huang, W., Zhang, J., Yang, T., Liu, J., Chui, C.K., Chang, S. (2010). Segmentation of gallbladder from CT images for a surgical training system. Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010 2 : 536-540. ScholarBank@NUS Repository. https://doi.org/10.1109/BMEI.2010.5639989
Abstract: A semi-automatic method was developed for the segmentation of 3D gallbladders (GB) from CT images, in order to construct a patient-specific model for a surgical training system. First a support vector machine (SVM) classifier was trained to extract GB region from one single 2D slice in the intermediate part of a GB by voxel classification. Then the extracted GB contour, after some morphological operations, was projected to the neighboring slices for automated re-sampling, learning and further voxel classification in these slices. This propagation procedure continued till all GB-containing slices were processed. The method was tested using 18 CT data sets and a set of quantitative measures were computed. The averaged volume overlap error of 15.56% and surface distance of 0.64 mm suggested that the method is efficient and promising. ©2010 IEEE.
Source Title: Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010
URI: http://scholarbank.nus.edu.sg/handle/10635/73830
ISBN: 9781424464968
DOI: 10.1109/BMEI.2010.5639989
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