Nature of Computation and Communication. International Conference, ICTCC 2014, Ho Chi Minh City, Vietnam, November 24-25, 2014, Revised Selected Papers

Research Article

Efficient Pancreas Segmentation in Computed Tomography Based on Region-Growing

Download
292 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-15392-6_31,
        author={Tran Tam and Nguyen Binh},
        title={Efficient Pancreas Segmentation in Computed Tomography Based on Region-Growing},
        proceedings={Nature of Computation and Communication. International Conference, ICTCC 2014, Ho Chi Minh City, Vietnam, November 24-25, 2014, Revised Selected Papers},
        proceedings_a={ICTCC},
        year={2015},
        month={2},
        keywords={Computed tomography Pancreas Segmentation Medical image},
        doi={10.1007/978-3-319-15392-6_31}
    }
    
  • Tran Tam
    Nguyen Binh
    Year: 2015
    Efficient Pancreas Segmentation in Computed Tomography Based on Region-Growing
    ICTCC
    ICST
    DOI: 10.1007/978-3-319-15392-6_31
Tran Tam1,*, Nguyen Binh1,*
  • 1: Ho Chi Minh City University of Technology
*Contact email: tamtd@hcmup.edu.vn, ntbinh@cse.hcmut.edu.vn

Abstract

Pancreas segmentation in computed tomography data is one of difficult problems in medical area. Segmentation of pancreas tissue in computed tomography is difficult even for human, since the pancreas head is always directly connected to the small bowel and can in most cases cannot be visually distinguished. In this paper, an efficient method to extract the pancreas from such computed tomography images is proposed. Histogram equalization is used to enhance the contrast of computed tomography images. After that, region-growing technique is applied to label pancreas region and return the result of segmentation. The proposed method will be experimented and evaluated by using Jaccard index between an extracted pancreas and a true one. For evaluating the proposed method, we have compared the results of our proposed method with the other recent methods available in literature.