한국멀티미디어학회논문지 (Journal of Korea Multimedia Society)

  • 제16권9호
  • /
  • Pages.1018-1030
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  • 2013
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  • 1229-7771(pISSN)
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  • 2384-0102(eISSN)
한국멀티미디어학회 (Korea Multimedia Society)
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Comparison of Active Contour and Active Shape Approaches for Corpus Callosum Segmentation

  • Adiya, Enkhbolor (Dept of Computer Engineering, Inje University) ;
  • Izmantoko, Yonny S. (Dept of Computer Engineering, Inje University) ;
  • Choi, Heung-Kook (Dept of Computer Engineering, UHRC, Inje University)
  • 투고 : 2013.05.09
  • 심사 : 2013.08.13
  • 발행 : 2013.09.30
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초록

The corpus callosum is the largest connective structure in the brain, and its shape and size are correlated to sex, age, brain growth and degeneration, handedness, musical ability, and neurological diseases. Manually segmenting the corpus callosum from brain magnetic resonance (MR) image is time consuming, error prone, and operator dependent. In this paper, two semi-automatic segmentation methods are present: the active contour model-based approach and the active shape model-based approach. We tested these methods on an MR image of the human brain and found that the active contour approach had better segmentation accuracy but was slower than the active shape approach.

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피인용 문헌

  1. Implementation of 2D Snake Model-based Segmentation on Corpus Callosum vol.17, pp.12, 2014, https://doi.org/10.9717/kmms.2014.17.12.1412
  2. Compar ison of Level Set-based Active Contour Models on Subcor tical Image Segmentation vol.18, pp.7, 2015, https://doi.org/10.9717/kmms.2015.18.7.827
  3. Semi-automated Approach to Hippocampus Segmentation Using Snake from Brain MRI vol.17, pp.5, 2014, https://doi.org/10.9717/kmms.2014.17.5.566
  4. Implementation of 2D Active Shape Model-based Segmentation on Hippocampus vol.17, pp.1, 2014, https://doi.org/10.9717/kmms.2014.17.1.001
  5. Classification of Brain MR Images Using Corpus Callosum Shape Measurements vol.4, pp.2, 2015, https://doi.org/10.4018/IJBCE.2015070105