Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function

N.F. Lori; R. Lavrador; L. Neto Fonseca; C. Santos; R. Travasso; A. Pereira; R. Rossetti; N. Sousa; V. Alves

doi:10.1007/978-3-319-31307-8_10

Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function

N.F. Lori
, R. Lavrador
, L. Neto Fonseca
, C. Santos
, R. Travasso
, A. Pereira
, R. Rossetti
, N. Sousa
, V. Alves

Cardiovascular Biomechanics

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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Diffusion MRI (dMRI) is highly sensitive in detecting early cerebral ischemic changes in acute stroke, and in pre-clinical assessment of white matter (WM) anatomy using tractography, thus being an important component of health informatics. In clinical settings, the computation time is critical, and so finding forms of reducing the processing time in high computation processes such as Diffusion Spectrum Imaging (DSI) dMRI data processing is extremely relevant. We analyse here a method for reducing the computation of the dMRI-based axonal orientation distribution function h by using a Monte Carlo sampling-based methods for voxel selection, and so obtained a reduction in required data sampling of about 20%. In this work we show that the convergence to the correct value in this type of dMRI data-processing is linear and not exponential, implying that the Monte Carlo approach in this type of dMRI data processing improves its speed, but further improvements are needed.

Originele taal-2	Engels
Titel	New Advances in Information Systems and Technologies, Vol. 2
Redacteuren	A. Rocha, A.M. Correia, H. Adeli, L.P. Reis, M.M. Teixeira
Plaats van productie	Berlin
Uitgeverij	Springer
Pagina's	95-105
Aantal pagina's	11
ISBN van elektronische versie	978-3-319-31307-8
ISBN van geprinte versie	9783319313061
DOI's	https://doi.org/10.1007/978-3-319-31307-8_10
Status	Gepubliceerd - 2016
Evenement	4th World Conference on Information Systems and Technologies (WorldCist 2016), March 22-24, 2016, Recife, Brazil - Mercure Recife Mar Hotel Conventions, Recife, Brazilië Duur: 22 mrt. 2016 → 24 mrt. 2016 https://worldcist2016.wordpress.com/

Publicatie series

Naam	Advances in Intelligent Systems and Computing
Volume	445
ISSN van geprinte versie	21945357

Congres

Congres	4th World Conference on Information Systems and Technologies (WorldCist 2016), March 22-24, 2016, Recife, Brazil
Verkorte titel	WorldCist 2016
Land/Regio	Brazilië
Stad	Recife
Periode	22/03/16 → 24/03/16
Internet adres	https://worldcist2016.wordpress.com/

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10.1007/978-3-319-31307-8_10

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Lori, N. F., Lavrador, R., Neto Fonseca, L., Santos, C., Travasso, R., Pereira, A., Rossetti, R., Sousa, N., & Alves, V. (2016). Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function. In A. Rocha, A. M. Correia, H. Adeli, L. P. Reis, & M. M. Teixeira (editors), New Advances in Information Systems and Technologies, Vol. 2 (blz. 95-105). (Advances in Intelligent Systems and Computing; Vol. 445). Springer. https://doi.org/10.1007/978-3-319-31307-8_10

Lori, N.F. ; Lavrador, R. ; Neto Fonseca, L. et al. / Reducing computation time by Monte Carlo method : an application in determining axonal orientation distribution function. New Advances in Information Systems and Technologies, Vol. 2 . redacteur / A. Rocha ; A.M. Correia ; H. Adeli ; L.P. Reis ; M.M. Teixeira. Berlin : Springer, 2016. blz. 95-105 (Advances in Intelligent Systems and Computing).

@inproceedings{f61841d407db473e8c9e88d37f05f8e0,

title = "Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function",

abstract = "Diffusion MRI (dMRI) is highly sensitive in detecting early cerebral ischemic changes in acute stroke, and in pre-clinical assessment of white matter (WM) anatomy using tractography, thus being an important component of health informatics. In clinical settings, the computation time is critical, and so finding forms of reducing the processing time in high computation processes such as Diffusion Spectrum Imaging (DSI) dMRI data processing is extremely relevant. We analyse here a method for reducing the computation of the dMRI-based axonal orientation distribution function h by using a Monte Carlo sampling-based methods for voxel selection, and so obtained a reduction in required data sampling of about 20\%. In this work we show that the convergence to the correct value in this type of dMRI data-processing is linear and not exponential, implying that the Monte Carlo approach in this type of dMRI data processing improves its speed, but further improvements are needed.",

keywords = "Axonal ODF, Diffusion MRI, Monte Carlo sampling methods, Optimization, White Matter",

author = "N.F. Lori and R. Lavrador and \{Neto Fonseca\}, L. and C. Santos and R. Travasso and A. Pereira and R. Rossetti and N. Sousa and V. Alves",

year = "2016",

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language = "English",

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series = "Advances in Intelligent Systems and Computing",

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booktitle = "New Advances in Information Systems and Technologies, Vol. 2",

address = "Germany",

note = "4th World Conference on Information Systems and Technologies (WorldCist 2016), March 22-24, 2016, Recife, Brazil, WorldCist 2016 ; Conference date: 22-03-2016 Through 24-03-2016",

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Lori, NF, Lavrador, R, Neto Fonseca, L, Santos, C, Travasso, R, Pereira, A, Rossetti, R, Sousa, N & Alves, V 2016, Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function. in A Rocha, AM Correia, H Adeli, LP Reis & MM Teixeira (reds.), New Advances in Information Systems and Technologies, Vol. 2 . Advances in Intelligent Systems and Computing, vol. 445, Springer, Berlin, blz. 95-105, 4th World Conference on Information Systems and Technologies (WorldCist 2016), March 22-24, 2016, Recife, Brazil, Recife, Brazilië, 22/03/16. https://doi.org/10.1007/978-3-319-31307-8_10

Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function. / Lori, N.F.; Lavrador, R.; Neto Fonseca, L. et al.
New Advances in Information Systems and Technologies, Vol. 2 . reds. / A. Rocha; A.M. Correia; H. Adeli; L.P. Reis; M.M. Teixeira. Berlin: Springer, 2016. blz. 95-105 (Advances in Intelligent Systems and Computing; Vol. 445).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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T1 - Reducing computation time by Monte Carlo method

T2 - 4th World Conference on Information Systems and Technologies (WorldCist 2016), March 22-24, 2016, Recife, Brazil

AU - Lori, N.F.

AU - Lavrador, R.

AU - Neto Fonseca, L.

AU - Santos, C.

AU - Travasso, R.

AU - Pereira, A.

AU - Rossetti, R.

AU - Sousa, N.

AU - Alves, V.

PY - 2016

Y1 - 2016

N2 - Diffusion MRI (dMRI) is highly sensitive in detecting early cerebral ischemic changes in acute stroke, and in pre-clinical assessment of white matter (WM) anatomy using tractography, thus being an important component of health informatics. In clinical settings, the computation time is critical, and so finding forms of reducing the processing time in high computation processes such as Diffusion Spectrum Imaging (DSI) dMRI data processing is extremely relevant. We analyse here a method for reducing the computation of the dMRI-based axonal orientation distribution function h by using a Monte Carlo sampling-based methods for voxel selection, and so obtained a reduction in required data sampling of about 20%. In this work we show that the convergence to the correct value in this type of dMRI data-processing is linear and not exponential, implying that the Monte Carlo approach in this type of dMRI data processing improves its speed, but further improvements are needed.

AB - Diffusion MRI (dMRI) is highly sensitive in detecting early cerebral ischemic changes in acute stroke, and in pre-clinical assessment of white matter (WM) anatomy using tractography, thus being an important component of health informatics. In clinical settings, the computation time is critical, and so finding forms of reducing the processing time in high computation processes such as Diffusion Spectrum Imaging (DSI) dMRI data processing is extremely relevant. We analyse here a method for reducing the computation of the dMRI-based axonal orientation distribution function h by using a Monte Carlo sampling-based methods for voxel selection, and so obtained a reduction in required data sampling of about 20%. In this work we show that the convergence to the correct value in this type of dMRI data-processing is linear and not exponential, implying that the Monte Carlo approach in this type of dMRI data processing improves its speed, but further improvements are needed.

KW - Axonal ODF

KW - Diffusion MRI

KW - Monte Carlo sampling methods

KW - Optimization

KW - White Matter

UR - https://www.scopus.com/pages/publications/84961665228

U2 - 10.1007/978-3-319-31307-8_10

DO - 10.1007/978-3-319-31307-8_10

M3 - Conference contribution

AN - SCOPUS:84961665228

SN - 9783319313061

T3 - Advances in Intelligent Systems and Computing

SP - 95

EP - 105

BT - New Advances in Information Systems and Technologies, Vol. 2

A2 - Rocha, A.

A2 - Correia, A.M.

A2 - Adeli, H.

A2 - Reis, L.P.

A2 - Teixeira, M.M.

PB - Springer

CY - Berlin

Y2 - 22 March 2016 through 24 March 2016

ER -

Lori NF, Lavrador R, Neto Fonseca L, Santos C, Travasso R, Pereira A et al. Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function. In Rocha A, Correia AM, Adeli H, Reis LP, Teixeira MM, redacteurs, New Advances in Information Systems and Technologies, Vol. 2 . Berlin: Springer. 2016. blz. 95-105. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-31307-8_10

Reducing computation time by Monte Carlo method: an application in determining axonal orientation distribution function

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