Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging

Khoi Minh Huynh; Ye Wu; Kim Han Thung; Sahar Ahmad; Hoyt Patrick Taylor IV; Dinggang Shen; Pew Thian Yap

doi:10.1007/978-3-030-59728-3_35

Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging

Khoi Minh Huynh, Ye Wu, Kim Han Thung, Sahar Ahmad, Hoyt Patrick Taylor IV, Dinggang Shen, Pew Thian Yap

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Most brain microstructure models are dedicated to the quantification of white matter microstructure, using for example sticks, cylinders, and zeppelins to model intra- and extra-axonal environments. Gray matter presents unique micro-architecture with cell bodies (somas) exhibiting diffusion characteristics that differ from axons in white matter. In this paper, we introduce a method to quantify soma microstructure, giving measures such as volume fraction, diffusivity, and kurtosis. Our method captures a spectrum of diffusion patterns and scales and does not rely on restrictive model assumptions. We show that our method yields unique and meaningful contrasts that are in agreement with histological data. We demonstrate its application in the mapping of the distinct spatial patterns of soma density in the cortex.

Original language	English
Title of host publication	Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings
Editors	Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	354-363
Number of pages	10
ISBN (Print)	9783030597276
DOIs	https://doi.org/10.1007/978-3-030-59728-3_35
Publication status	Published - 2020
Externally published	Yes
Event	23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 - Lima, Peru Duration: 2020 Oct 4 → 2020 Oct 8

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12267 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020
Country	Peru
City	Lima
Period	20/10/4 → 20/10/8

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-030-59728-3_35

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Huynh, K. M., Wu, Y., Thung, K. H., Ahmad, S., Taylor IV, H. P., Shen, D., & Yap, P. T. (2020). Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging. In A. L. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. A. Zuluaga, S. K. Zhou, D. Racoceanu, & L. Joskowicz (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings (pp. 354-363). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12267 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59728-3_35

Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging. / Huynh, Khoi Minh; Wu, Ye; Thung, Kim Han; Ahmad, Sahar; Taylor IV, Hoyt Patrick; Shen, Dinggang; Yap, Pew Thian.

Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. ed. / Anne L. Martel; Purang Abolmaesumi; Danail Stoyanov; Diana Mateus; Maria A. Zuluaga; S. Kevin Zhou; Daniel Racoceanu; Leo Joskowicz. Springer Science and Business Media Deutschland GmbH, 2020. p. 354-363 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12267 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Huynh, KM, Wu, Y, Thung, KH, Ahmad, S, Taylor IV, HP, Shen, D & Yap, PT 2020, Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging. in AL Martel, P Abolmaesumi, D Stoyanov, D Mateus, MA Zuluaga, SK Zhou, D Racoceanu & L Joskowicz (eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12267 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 354-363, 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, Lima, Peru, 20/10/4. https://doi.org/10.1007/978-3-030-59728-3_35

Huynh KM, Wu Y, Thung KH, Ahmad S, Taylor IV HP, Shen D et al. Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging. In Martel AL, Abolmaesumi P, Stoyanov D, Mateus D, Zuluaga MA, Zhou SK, Racoceanu D, Joskowicz L, editors, Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 354-363. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-59728-3_35

Huynh, Khoi Minh ; Wu, Ye ; Thung, Kim Han ; Ahmad, Sahar ; Taylor IV, Hoyt Patrick ; Shen, Dinggang ; Yap, Pew Thian. / Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. editor / Anne L. Martel ; Purang Abolmaesumi ; Danail Stoyanov ; Diana Mateus ; Maria A. Zuluaga ; S. Kevin Zhou ; Daniel Racoceanu ; Leo Joskowicz. Springer Science and Business Media Deutschland GmbH, 2020. pp. 354-363 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Most brain microstructure models are dedicated to the quantification of white matter microstructure, using for example sticks, cylinders, and zeppelins to model intra- and extra-axonal environments. Gray matter presents unique micro-architecture with cell bodies (somas) exhibiting diffusion characteristics that differ from axons in white matter. In this paper, we introduce a method to quantify soma microstructure, giving measures such as volume fraction, diffusivity, and kurtosis. Our method captures a spectrum of diffusion patterns and scales and does not rely on restrictive model assumptions. We show that our method yields unique and meaningful contrasts that are in agreement with histological data. We demonstrate its application in the mapping of the distinct spatial patterns of soma density in the cortex.",

author = "Huynh, {Khoi Minh} and Ye Wu and Thung, {Kim Han} and Sahar Ahmad and {Taylor IV}, {Hoyt Patrick} and Dinggang Shen and Yap, {Pew Thian}",

note = "Funding Information: This work was supported in part by NIH grants (NS093842 and EB022880). Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 ; Conference date: 04-10-2020 Through 08-10-2020",

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Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging

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