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|Title:||Segmentation of gallbladder from CT images for a surgical training system||Authors:||Zhou, J.
Image-guided surgical training
Support vector machine (SVM)
|Issue Date:||2010||Citation:||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|
|Appears in Collections:||Staff Publications|
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