Rank-2 model-order selection in diffusion tensor MRI: Infromation complexity based on the total Kullback-Leibler divergence

Jianfei Yang; Dirk H.J. Poot; Matthan W.A. Caan; Frans M. Vos; Lucas J. Van Vliet

doi:10.1109/ISBI.2015.7164022

Rank-2 model-order selection in diffusion tensor MRI: Infromation complexity based on the total Kullback-Leibler divergence

Jianfei Yang^*, Dirk H.J. Poot, Matthan W.A. Caan, Frans M. Vos, Lucas J. Van Vliet

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Academic › peer-review

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Abstract

Diffusion-weighted MRI (DW-MRI) can assess the integrity of white matter (WM) structures in the human brain. Multi-compartment analysis of DW-MRI requires an estimate of the number of compartments to permit unbiased estimation of the diffusion shape in a single fibers as well as crossing fascicles. We propose a new, rotation-invariant measure to assess the suitability of a model by a measure for information complexity (ICOMP) based on the total Kullback-Leibler divergence (TKLD). ICOMP-TKLD is evaluated on simulated data and on data from the Human Connectome Project. Compared to the state-of-the-art, ICOMP-TKLD is the only method that yields reliable model-order selection in both homogeneous and heterogeneous WM regions. Therefore, ICOM-TKLD may open the way for structure-adaptive estimation of diffusion properties of the entire brain.

Original language	English
Pages (from-to)	926-929
Number of pages	4
Journal	Proceedings - International Symposium on Biomedical Imaging
DOIs	https://doi.org/10.1109/ISBI.2015.7164022
Publication status	Published - 21 Jul 2015
Event	12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States Duration: 16 Apr 2015 → 19 Apr 2015

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© 2015 IEEE.

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10.1109/ISBI.2015.7164022

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title = "Rank-2 model-order selection in diffusion tensor MRI: Infromation complexity based on the total Kullback-Leibler divergence",

abstract = "Diffusion-weighted MRI (DW-MRI) can assess the integrity of white matter (WM) structures in the human brain. Multi-compartment analysis of DW-MRI requires an estimate of the number of compartments to permit unbiased estimation of the diffusion shape in a single fibers as well as crossing fascicles. We propose a new, rotation-invariant measure to assess the suitability of a model by a measure for information complexity (ICOMP) based on the total Kullback-Leibler divergence (TKLD). ICOMP-TKLD is evaluated on simulated data and on data from the Human Connectome Project. Compared to the state-of-the-art, ICOMP-TKLD is the only method that yields reliable model-order selection in both homogeneous and heterogeneous WM regions. Therefore, ICOM-TKLD may open the way for structure-adaptive estimation of diffusion properties of the entire brain.",

author = "Jianfei Yang and Poot, {Dirk H.J.} and Caan, {Matthan W.A.} and Vos, {Frans M.} and {Van Vliet}, {Lucas J.}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",

year = "2015",

month = jul,

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doi = "10.1109/ISBI.2015.7164022",

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T2 - 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015

AU - Yang, Jianfei

AU - Poot, Dirk H.J.

AU - Caan, Matthan W.A.

AU - Vos, Frans M.

AU - Van Vliet, Lucas J.

PY - 2015/7/21

Y1 - 2015/7/21

N2 - Diffusion-weighted MRI (DW-MRI) can assess the integrity of white matter (WM) structures in the human brain. Multi-compartment analysis of DW-MRI requires an estimate of the number of compartments to permit unbiased estimation of the diffusion shape in a single fibers as well as crossing fascicles. We propose a new, rotation-invariant measure to assess the suitability of a model by a measure for information complexity (ICOMP) based on the total Kullback-Leibler divergence (TKLD). ICOMP-TKLD is evaluated on simulated data and on data from the Human Connectome Project. Compared to the state-of-the-art, ICOMP-TKLD is the only method that yields reliable model-order selection in both homogeneous and heterogeneous WM regions. Therefore, ICOM-TKLD may open the way for structure-adaptive estimation of diffusion properties of the entire brain.

AB - Diffusion-weighted MRI (DW-MRI) can assess the integrity of white matter (WM) structures in the human brain. Multi-compartment analysis of DW-MRI requires an estimate of the number of compartments to permit unbiased estimation of the diffusion shape in a single fibers as well as crossing fascicles. We propose a new, rotation-invariant measure to assess the suitability of a model by a measure for information complexity (ICOMP) based on the total Kullback-Leibler divergence (TKLD). ICOMP-TKLD is evaluated on simulated data and on data from the Human Connectome Project. Compared to the state-of-the-art, ICOMP-TKLD is the only method that yields reliable model-order selection in both homogeneous and heterogeneous WM regions. Therefore, ICOM-TKLD may open the way for structure-adaptive estimation of diffusion properties of the entire brain.

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U2 - 10.1109/ISBI.2015.7164022

DO - 10.1109/ISBI.2015.7164022

M3 - Conference article

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SN - 1945-7928

SP - 926

EP - 929

JO - Proceedings - International Symposium on Biomedical Imaging

JF - Proceedings - International Symposium on Biomedical Imaging

Y2 - 16 April 2015 through 19 April 2015

ER -

Rank-2 model-order selection in diffusion tensor MRI: Infromation complexity based on the total Kullback-Leibler divergence

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