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Semiautomatic segmentation of brain subcortical structures from high-field MRI.

Publication ,  Journal Article
Kim, J; Lenglet, C; Duchin, Y; Sapiro, G; Harel, N
Published in: IEEE journal of biomedical and health informatics
September 2014

Volumetric segmentation of subcortical structures, such as the basal ganglia and thalamus, is necessary for noninvasive diagnosis and neurosurgery planning. This is a challenging problem due in part to limited boundary information between structures, similar intensity profiles across the different structures, and low contrast data. This paper presents a semiautomatic segmentation system exploiting the superior image quality of ultrahigh field (7 T) MRI. The proposed approach utilizes the complementary edge information in the multiple structural MRI modalities. It combines optimally selected two modalities from susceptibility-weighted, T2-weighted, and diffusion MRI, and introduces a tailored new edge indicator function. In addition to this, we employ prior shape and configuration knowledge of the subcortical structures in order to guide the evolution of geometric active surfaces. Neighboring structures are segmented iteratively, constraining oversegmentation at their borders with a nonoverlapping penalty. Several experiments with data acquired on a 7 T MRI scanner demonstrate the feasibility and power of the approach for the segmentation of basal ganglia components critical for neurosurgery applications such as deep brain stimulation surgery.

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Published In

IEEE journal of biomedical and health informatics

DOI

EISSN

2168-2208

ISSN

2168-2194

Publication Date

September 2014

Volume

18

Issue

5

Start / End Page

1678 / 1695

Related Subject Headings

  • Thalamus
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Brain
  • Basal Ganglia
  • Algorithms
 

Citation

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Kim, J., Lenglet, C., Duchin, Y., Sapiro, G., & Harel, N. (2014). Semiautomatic segmentation of brain subcortical structures from high-field MRI. IEEE Journal of Biomedical and Health Informatics, 18(5), 1678–1695. https://doi.org/10.1109/jbhi.2013.2292858
Kim, Jinyoung, Christophe Lenglet, Yuval Duchin, Guillermo Sapiro, and Noam Harel. “Semiautomatic segmentation of brain subcortical structures from high-field MRI.IEEE Journal of Biomedical and Health Informatics 18, no. 5 (September 2014): 1678–95. https://doi.org/10.1109/jbhi.2013.2292858.
Kim J, Lenglet C, Duchin Y, Sapiro G, Harel N. Semiautomatic segmentation of brain subcortical structures from high-field MRI. IEEE journal of biomedical and health informatics. 2014 Sep;18(5):1678–95.
Kim, Jinyoung, et al. “Semiautomatic segmentation of brain subcortical structures from high-field MRI.IEEE Journal of Biomedical and Health Informatics, vol. 18, no. 5, Sept. 2014, pp. 1678–95. Epmc, doi:10.1109/jbhi.2013.2292858.
Kim J, Lenglet C, Duchin Y, Sapiro G, Harel N. Semiautomatic segmentation of brain subcortical structures from high-field MRI. IEEE journal of biomedical and health informatics. 2014 Sep;18(5):1678–1695.

Published In

IEEE journal of biomedical and health informatics

DOI

EISSN

2168-2208

ISSN

2168-2194

Publication Date

September 2014

Volume

18

Issue

5

Start / End Page

1678 / 1695

Related Subject Headings

  • Thalamus
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Brain
  • Basal Ganglia
  • Algorithms