Parcellation of human amygdala subfields using orientation distribution function and spectral k-means clustering

Qiuting Wen, Brian D. Stirling, Long Sha, Li Shen, Paul J. Whalen, Yu-Chien Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Amygdala plays an important role in fear and emotional learning, which are critical for human survival. Despite the functional relevance and unique circuitry of each human amygdaloid subnuclei, there has yet to be an efficient imaging method for identifying these regions in vivo. A data-driven approach without prior knowledge provides advantages of efficient and objective assessments. The present study uses high angular and high spatial resolution diffusion magnetic resonance imaging to generate orientation distribution function, which bears distinctive microstructural features. The features were extracted using spherical harmonic decomposition to assess microstructural similarity within amygdala subfields that are identified via similarity matrices using spectral k-mean clustering. The approach was tested on 32 healthy volunteers and three distinct amygdala subfields were identified including medial, posterior-superior lateral, and anterior-inferior lateral.

Original languageEnglish (US)
Title of host publicationComputational Diffusion MRI - MICCAI Workshop
PublisherSpringer Heidelberg
Pages123-132
Number of pages10
VolumePart F2
ISBN (Print)9783319541297
DOIs
StatePublished - 2017
EventMICCAI Workshop on Computational Diffusion MRI, CDMRI 2016 - Athens, Greece
Duration: Oct 17 2016Oct 21 2016

Publication series

NameMathematics and Visualization
VolumePart F2
ISSN (Print)1612-3786
ISSN (Electronic)2197-666X

Other

OtherMICCAI Workshop on Computational Diffusion MRI, CDMRI 2016
CountryGreece
CityAthens
Period10/17/1610/21/16

Fingerprint

Spectral Clustering
K-means Clustering
Subfield
Distribution functions
Lateral
Distribution Function
Imaging techniques
Spherical Harmonics
Magnetic Resonance Imaging
Magnetic resonance
Prior Knowledge
Data-driven
Spatial Resolution
High Resolution
Imaging
Decomposition
Distinct
Decompose
Human
Similarity

ASJC Scopus subject areas

  • Modeling and Simulation
  • Geometry and Topology
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics

Cite this

Wen, Q., Stirling, B. D., Sha, L., Shen, L., Whalen, P. J., & Wu, Y-C. (2017). Parcellation of human amygdala subfields using orientation distribution function and spectral k-means clustering. In Computational Diffusion MRI - MICCAI Workshop (Vol. Part F2, pp. 123-132). (Mathematics and Visualization; Vol. Part F2). Springer Heidelberg. https://doi.org/10.1007/978-3-319-54130-3_10

Parcellation of human amygdala subfields using orientation distribution function and spectral k-means clustering. / Wen, Qiuting; Stirling, Brian D.; Sha, Long; Shen, Li; Whalen, Paul J.; Wu, Yu-Chien.

Computational Diffusion MRI - MICCAI Workshop. Vol. Part F2 Springer Heidelberg, 2017. p. 123-132 (Mathematics and Visualization; Vol. Part F2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wen, Q, Stirling, BD, Sha, L, Shen, L, Whalen, PJ & Wu, Y-C 2017, Parcellation of human amygdala subfields using orientation distribution function and spectral k-means clustering. in Computational Diffusion MRI - MICCAI Workshop. vol. Part F2, Mathematics and Visualization, vol. Part F2, Springer Heidelberg, pp. 123-132, MICCAI Workshop on Computational Diffusion MRI, CDMRI 2016, Athens, Greece, 10/17/16. https://doi.org/10.1007/978-3-319-54130-3_10
Wen Q, Stirling BD, Sha L, Shen L, Whalen PJ, Wu Y-C. Parcellation of human amygdala subfields using orientation distribution function and spectral k-means clustering. In Computational Diffusion MRI - MICCAI Workshop. Vol. Part F2. Springer Heidelberg. 2017. p. 123-132. (Mathematics and Visualization). https://doi.org/10.1007/978-3-319-54130-3_10
Wen, Qiuting ; Stirling, Brian D. ; Sha, Long ; Shen, Li ; Whalen, Paul J. ; Wu, Yu-Chien. / Parcellation of human amygdala subfields using orientation distribution function and spectral k-means clustering. Computational Diffusion MRI - MICCAI Workshop. Vol. Part F2 Springer Heidelberg, 2017. pp. 123-132 (Mathematics and Visualization).
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