Browse > Article
http://dx.doi.org/10.6109/jkiice.2012.16.8.1765

Segmentation and 3-Dimensional Reconstruction of Liver using MeVisLab  

Shin, Min-Jun (순천대학교 컴퓨터과학과)
Kim, Do-Yeon (순천대학교 컴퓨터공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.16, no.8, 2012 , pp. 1765-1772 More about this Journal
Abstract
Success rate of transplantation of body organs improved due to development of medical equipment and diagnostic technology. In particular, a liver transplant due to liver dysfunction has increased. With the development of image processing and analysis to obtain the volume for liver transplantation have increased the accuracy and efficiency. In this thesis, we try to reconstruct the regions of the liver within three dimensional images using the mevislab tool, which is effective in quick comparison and analysis of various algorithms, and in expedient development of prototypes. Liver is divided by applying threshold values and region growing method to the original image, and by removing noise and unnecessary entities through morphology and region filling, and setting of areas of interest. It is deemed that high temporal efficiency, and presentation of diverse range of comparison and analysis module application methods through usage of MeVisLab would make contribution towards expanding of baseline of medical image processing researches.
Keywords
Image Segmentation; MeVisLab; Liver; 3D reconstruction;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 MEVIS Medical Solutions, "First Steps with MeVisLab", MeVis Medical Solutions, 2011
2 Chen Zhaoxue, Qian Lijun, "Automatic Liver Segmentation Method Based on a Gaussian Blurring Technique For CT Images", Bio informatics and Biomedical Engineering, ICBBE 2008, pp. 2516-2518, 2008
3 강정현, "MDCT 영상에서 간 추출 및 분할", 충남대학교, 2005
4 Yufei Chen, Zhicheng Wang, Weidong Zhao, Xiaochun Yang, "Liver Segmentation from CT Images Based on Region Growing Method", Bioinformatics and Biomedical Engineering, ICBBE 2009, pp. 1-4, 2009
5 Suhuai Luo, Jesse S. Jin, Stephan K. Chalup, Guoyu Qian, "A Liver Segmentation Algorithm Based on Wavelets and Machine Learning", Computational Intelligence and Natural Computing, CINC 2009, pp 122-125 2009
6 Tianyi Gui, Lin-Lin Huang, Akinobu Shimizu, "Liver Segmentation for CT Images using an Improved GGVF-Snake", SICE, pp. 676-681, 2007
7 Yufei Chen, Zhicheng Wang, Weidong Zhao, "Liver segmentation in CT images using Chan-Vese Model", Information Science and Engineering (ICISE), pp 3669-3672, 2009
8 Samuel Silva, Beatriz Sousa Santos, Joaquim Madeira, Augusto Silva, "Processing Visualization and Analysis of Medical Images of the Heart: An Example of Fast Prototyping using MeVisLab", Visualisation, VIZ '09, pp 165-170, 2009
9 신민준, 김도연, "흉부 MDCT 영상을 이용한 신체 장기의 단계별 분할", 멀티미디어학 회논문지, 제14권 제11호, 2011   과학기술학회마을   DOI   ScienceOn