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International Conference on Health Information Science

HIS 2016: Health Information Science pp 22–30Cite as

Improved GrabCut for Human Brain Computerized Tomography Image Segmentation

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10038))

Abstract

In this paper, we modified GrabCut for gray-scale slice-stacked medical image segmentation. First, GrabCut was extended from planar to volume image processing. Second, we simplified manual interaction by drawing a polygon for one volume instead of a rectangle. After that, twenty human brain computerized tomography images were analyzed. Experimental results show that the modified algorithm is simple and fast, and enhances segmentation accuracy compared with the confidence connection algorithm. Moreover, the algorithm is reproducible with respect to different users and consequently it can release physicians from this kind of time-consuming and laborious tasks. In addition, this method can be used for other types of medical volume image segmentation.

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Acknowledgment

This work is supported by grants from National Natural Science Foundation of China (Grant No. 81501463), Guangdong Innovative Research Team Program (Grant No. 2011S013), National 863 Programs of China (Grant No. 2015AA043203), Shenzhen Fundamental Research Program (Grant Nos. JCYJ20140417113430726, JCYJ20140417113430665 and JCYJ201500731154850923) and Beijing Center for Mathematics and Information Interdisciplinary Sciences.

Author information

Authors and Affiliations

  1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Zhihua Ji, Shaode Yu, Shibin Wu & Yaoqin Xie

  2. Academy of Big Data and Information Engineering, Guizhou University, Guiyang, China

    Zhihua Ji & Fashun Yang

  3. Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, 518055, China

    Shaode Yu & Shibin Wu

Authors
  1. Zhihua Ji
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  2. Shaode Yu
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  3. Shibin Wu
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  4. Yaoqin Xie
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  5. Fashun Yang
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Corresponding author

Correspondence to Shaode Yu .

Editor information

Editors and Affiliations

  1. Victoria University , Melbourne, Australia

    Xiaoxia Yin

  2. Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA

    James Geller

  3. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Ye Li

  4. Victoria University , Melbourne, Australia

    Rui Zhou

  5. Centre for Applied Informatics, Victoria University, Melbourne, Australia

    Hua Wang

  6. Centre for Applied Informatics, Victoria University, Melbourne, Australia

    Yanchun Zhang

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© 2016 Springer International Publishing AG

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Ji, Z., Yu, S., Wu, S., Xie, Y., Yang, F. (2016). Improved GrabCut for Human Brain Computerized Tomography Image Segmentation. In: Yin, X., Geller, J., Li, Y., Zhou, R., Wang, H., Zhang, Y. (eds) Health Information Science. HIS 2016. Lecture Notes in Computer Science(), vol 10038. Springer, Cham. https://doi.org/10.1007/978-3-319-48335-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-48335-1_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48334-4

  • Online ISBN: 978-3-319-48335-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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