Automatic slice growing method based 3D reconstruction of liver with its vessels
Date
2014Publisher
© 2014 Institute of Electrical and Electronics Engineers Inc.Metadata
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Alom, M. Z., Mostakim, M., Biswas, R., & Chakrabarty, A. (2014). Automatic slice growing method based 3D reconstruction of liver with its vessels. Paper presented at the 16th Int'l Conf. Computer and Information Technology, ICCIT 2013, 338-344. doi:10.1109/ICCITechn.2014.6997361Abstract
In the recent years, reconstructing 3D liver and its vessels from abdominal CT volume images becomes an inevitable and necessary research field. In this paper, a method of 3D reconstruction of liver with its vessels has been implemented, which involves volume preprocessing, de-noising, segmentation, contouring, and combination of different modalities. An advanced liver segmentation algorithms have been proposed: The first one is a 2.5D method that utilizes automatic Slice Growing Method (SGM) to segment liver part of each slice of a data set. It takes advantage of curvature control of level set segmentation method to distinguish liver and adjacent organs. It is proved that the result of this proposed method is much better than simple 3D level set method in liver segmentation. In the case of liver vessel segmentation, we have proposed an improved smoothing method dedicate to 3D vascular volume which results from region growing segmentation method. The cooperation of region growing method and proposed smoothing method has been demonstrated the possibility of efficient vessel segmentation with very accurate results. And the results indicate that our method is suitable for anatomical studying and surgical planning.
Description
This conference paper was presented in 16th International Conference on Computer and Information Technology, ICCIT 2013; Khulna; Bangladesh; 8 March 2014 through 10 March 2014 [© 2014 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/ICCITechn.2014.6997361Publisher Link
http://ieeexplore.ieee.org/document/6997361/Department
Department of Computer Science and Engineering, BRAC UniversityType
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