Reconstruction of convex polynomial diffusion MRI models using semi-definite programming

T.C.J. Dela Haije; A. Fuster; L.M.J. Florack

Reconstruction of convex polynomial diffusion MRI models using semi-definite programming

T.C.J. Dela Haije, A. Fuster, L.M.J. Florack

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

Abstract

In this work we describe and perform the reconstruction of general polynomial diffusion MRI models, with the added constraint that the polynomials are convex. This is done by requiring the Hessian of the model to be sum-of-squares. The resulting optimization problem is shown to be solvable in a reasonable amount of time for the scale of data typical in clinical diffusion MRI acquisitions.

Original language	English
Title of host publication	Proceedings of the 23rd Annual Meeting of the ISMRM, Toronto, Canada
Pages	2821
Publication status	Published - 2015
Event	23rd ISMRM Annual Meeting and Exhibition, May 30-June 6, 2015, Toronto, Canada - Toronto, Canada Duration: 30 May 2015 → 5 Jun 2015 http://www.ismrm.org/15/program_files/ThuTP02.htm

Conference

Conference	23rd ISMRM Annual Meeting and Exhibition, May 30-June 6, 2015, Toronto, Canada
Abbreviated title	ISMRM2015
Country/Territory	Canada
City	Toronto
Period	30/05/15 → 5/06/15
Internet address	http://www.ismrm.org/15/program_files/ThuTP02.htm

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@inproceedings{30fd839cc1e843fda49b42d63d82af00,

title = "Reconstruction of convex polynomial diffusion MRI models using semi-definite programming",

abstract = "In this work we describe and perform the reconstruction of general polynomial diffusion MRI models, with the added constraint that the polynomials are convex. This is done by requiring the Hessian of the model to be sum-of-squares. The resulting optimization problem is shown to be solvable in a reasonable amount of time for the scale of data typical in clinical diffusion MRI acquisitions.",

author = "{Dela Haije}, T.C.J. and A. Fuster and L.M.J. Florack",

year = "2015",

language = "English",

pages = "2821",

booktitle = "Proceedings of the 23rd Annual Meeting of the ISMRM, Toronto, Canada",

note = "23rd ISMRM Annual Meeting and Exhibition, May 30-June 6, 2015, Toronto, Canada, ISMRM2015 ; Conference date: 30-05-2015 Through 05-06-2015",

url = "http://www.ismrm.org/15/program_files/ThuTP02.htm",

}

Dela Haije, TCJ, Fuster, A & Florack, LMJ 2015, Reconstruction of convex polynomial diffusion MRI models using semi-definite programming. in Proceedings of the 23rd Annual Meeting of the ISMRM, Toronto, Canada. pp. 2821, 23rd ISMRM Annual Meeting and Exhibition, May 30-June 6, 2015, Toronto, Canada, Toronto, Canada, 30/05/15. <http://www.ismrm.org/15/program_files/ThuTP02.htm>

TY - GEN

T1 - Reconstruction of convex polynomial diffusion MRI models using semi-definite programming

AU - Dela Haije, T.C.J.

AU - Fuster, A.

AU - Florack, L.M.J.

PY - 2015

Y1 - 2015

N2 - In this work we describe and perform the reconstruction of general polynomial diffusion MRI models, with the added constraint that the polynomials are convex. This is done by requiring the Hessian of the model to be sum-of-squares. The resulting optimization problem is shown to be solvable in a reasonable amount of time for the scale of data typical in clinical diffusion MRI acquisitions.

AB - In this work we describe and perform the reconstruction of general polynomial diffusion MRI models, with the added constraint that the polynomials are convex. This is done by requiring the Hessian of the model to be sum-of-squares. The resulting optimization problem is shown to be solvable in a reasonable amount of time for the scale of data typical in clinical diffusion MRI acquisitions.

M3 - Conference contribution

SP - 2821

BT - Proceedings of the 23rd Annual Meeting of the ISMRM, Toronto, Canada

T2 - 23rd ISMRM Annual Meeting and Exhibition, May 30-June 6, 2015, Toronto, Canada

Y2 - 30 May 2015 through 5 June 2015

ER -

Reconstruction of convex polynomial diffusion MRI models using semi-definite programming

Abstract

Conference

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