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Volume segmentation in medical image analysis: a survey

Published: 26 February 2010 Publication History

Abstract

Volume segmentation is an important part of computer based medical applications for diagnosis and analysis of anatomical data. With rapid advances in medical imaging modalities and volume visualization techniques, computer based diagnosis is fast becoming a reality. These computer based tools allow scientists and physician to understand and diagnose anatomical structures by virtually interacting with them. Volume segmentation plays a critical role by facilitating automatic or semiautomatic extraction of the anatomical organ or region of interest. In this review we provide an introduction to various segmentation algorithms found in the literature. We classify the algorithms in to three categories: structural techniques, statistical technique and hybrid techniques. Under structural techniques we will review algorithms which take into consideration structural information for segmentation stochastic techniques are those which perform segmentation based on statistical analysis methods and under hybrid techniques we will review algorithms which make use of structural information in addition to statistical analysis.

References

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J. A. sethian. Levelset methods Cambridge university 1999.
[2]
3d segmentation technique by saran lakare dec 2000.
[3]
Image processing fundamentals http://www.ph.tn.tudelft.nl/Courses/FIP/noframes/fip-Smoothin.html
[4]
Snakes: active contour models in international journal of computer vision
[5]
IEEE Transactions on medical imaging vol 16 no. 2, april 1997
[6]
Survey 3d image segmentation method by fraunhofer 2007.Shape-specifiic adaptations for levelset deformable model based segmentation Marko Subasic1, Sven Loncaric1 and Erich Sorantin2

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  • (2014)Half Century for Image SegmentationEncyclopedia of Information Science and Technology, Third Edition10.4018/978-1-4666-5888-2.ch584(5906-5915)Online publication date: 31-Jul-2014

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cover image ACM Other conferences
ICWET '10: Proceedings of the International Conference and Workshop on Emerging Trends in Technology
February 2010
1070 pages
ISBN:9781605588124
DOI:10.1145/1741906
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • UNITECH: Unitech Engineers, India
  • AICTE: All India Council for Technical Education

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 February 2010

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Author Tags

  1. application
  2. segmentation
  3. three techniques
  4. volume segmentation

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ICWET '10
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  • UNITECH
  • AICTE

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Cited By

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  • (2014)Half Century for Image SegmentationEncyclopedia of Information Science and Technology, Third Edition10.4018/978-1-4666-5888-2.ch584(5906-5915)Online publication date: 31-Jul-2014

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