Improved reference tracts for unsupervised brain white matter tractography

Susana Muñoz Maniega; Mark Bastin; Ian Deary; Joanna Wardlaw; Jonathan D. Clayden

doi:10.1007/978-3-319-60964-5_37

Improved reference tracts for unsupervised brain white matter tractography

Susana Muñoz Maniega, Mark Bastin, Ian Deary, Joanna Wardlaw, Jonathan D. Clayden

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

Abstract / Description of output

Neighbourhood tractography aims to automatically segment equivalent brain white matter tracts from diffusion magnetic resonance imaging (dMRI) data in different subjects by using a “reference tract” as a prior for the shape and length of each tract of interest. In the current work we present a means of improving the technique by using references tracts derived from dMRI data acquired from 80 healthy volunteers aged 25–64 years. The reference tracts were tested on the segmentation of 16 major white matter tracts in 50 healthy older people, aged 71.8 (±0.4) years. We found that datagenerated reference tracts improved the automatic white matter tract segmentations compared to results from atlas-generated reference tracts. We also obtained higher percentages of visually acceptable segmented tracts and lower variation in water diffusion parameters using this approach.

Original language	English
Title of host publication	Medical Image Understanding and Analysis
Subtitle of host publication	21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings
Pages	425-435
DOIs	https://doi.org/10.1007/978-3-319-60964-5_37
Publication status	E-pub ahead of print - 22 Jun 2017

Publication series

Name	Communications in Computer and Information Science

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10.1007/978-3-319-60964-5_37

Improved reference tracts for unsupervised brain white matter tractography
This is author's manuscript as accepted for publication
Accepted author manuscript, 1.24 MB

https://link.springer.com/chapter/10.1007/978-3-319-60964-5_37

RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.
Deary, I., Gale, C., Holmes, M., Logie, P., Maclullich, A., Porteous, D., Seckl, J., Starr, J., Wardlaw, J. & Okely, J.
1/09/13 → 31/08/19
Project: Research

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Muñoz Maniega, S., Bastin, M., Deary, I., Wardlaw, J., & Clayden, J. D. (2017). Improved reference tracts for unsupervised brain white matter tractography. In Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings (pp. 425-435). (Communications in Computer and Information Science). Advance online publication. https://doi.org/10.1007/978-3-319-60964-5_37

@inproceedings{4f79ee3df50f479192785391e395a219,

title = "Improved reference tracts for unsupervised brain white matter tractography",

abstract = "Neighbourhood tractography aims to automatically segment equivalent brain white matter tracts from diffusion magnetic resonance imaging (dMRI) data in different subjects by using a “reference tract” as a prior for the shape and length of each tract of interest. In the current work we present a means of improving the technique by using references tracts derived from dMRI data acquired from 80 healthy volunteers aged 25–64 years. The reference tracts were tested on the segmentation of 16 major white matter tracts in 50 healthy older people, aged 71.8 (±0.4) years. We found that datagenerated reference tracts improved the automatic white matter tract segmentations compared to results from atlas-generated reference tracts. We also obtained higher percentages of visually acceptable segmented tracts and lower variation in water diffusion parameters using this approach.",

author = "{Mu{\~n}oz Maniega}, Susana and Mark Bastin and Ian Deary and Joanna Wardlaw and Clayden, {Jonathan D.}",

year = "2017",

month = jun,

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doi = "10.1007/978-3-319-60964-5_37",

language = "English",

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Muñoz Maniega, S , Bastin, M , Deary, I , Wardlaw, J & Clayden, JD 2017, Improved reference tracts for unsupervised brain white matter tractography. in Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings. Communications in Computer and Information Science, pp. 425-435. https://doi.org/10.1007/978-3-319-60964-5_37

Improved reference tracts for unsupervised brain white matter tractography. / Muñoz Maniega, Susana ; Bastin, Mark ; Deary, Ian et al.
Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings. 2017. p. 425-435 (Communications in Computer and Information Science).

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

TY - GEN

T1 - Improved reference tracts for unsupervised brain white matter tractography

AU - Muñoz Maniega, Susana

AU - Bastin, Mark

AU - Deary, Ian

AU - Wardlaw, Joanna

AU - Clayden, Jonathan D.

PY - 2017/6/22

Y1 - 2017/6/22

N2 - Neighbourhood tractography aims to automatically segment equivalent brain white matter tracts from diffusion magnetic resonance imaging (dMRI) data in different subjects by using a “reference tract” as a prior for the shape and length of each tract of interest. In the current work we present a means of improving the technique by using references tracts derived from dMRI data acquired from 80 healthy volunteers aged 25–64 years. The reference tracts were tested on the segmentation of 16 major white matter tracts in 50 healthy older people, aged 71.8 (±0.4) years. We found that datagenerated reference tracts improved the automatic white matter tract segmentations compared to results from atlas-generated reference tracts. We also obtained higher percentages of visually acceptable segmented tracts and lower variation in water diffusion parameters using this approach.

AB - Neighbourhood tractography aims to automatically segment equivalent brain white matter tracts from diffusion magnetic resonance imaging (dMRI) data in different subjects by using a “reference tract” as a prior for the shape and length of each tract of interest. In the current work we present a means of improving the technique by using references tracts derived from dMRI data acquired from 80 healthy volunteers aged 25–64 years. The reference tracts were tested on the segmentation of 16 major white matter tracts in 50 healthy older people, aged 71.8 (±0.4) years. We found that datagenerated reference tracts improved the automatic white matter tract segmentations compared to results from atlas-generated reference tracts. We also obtained higher percentages of visually acceptable segmented tracts and lower variation in water diffusion parameters using this approach.

U2 - 10.1007/978-3-319-60964-5_37

DO - 10.1007/978-3-319-60964-5_37

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T3 - Communications in Computer and Information Science

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BT - Medical Image Understanding and Analysis

ER -

Muñoz Maniega S , Bastin M , Deary I , Wardlaw J, Clayden JD. Improved reference tracts for unsupervised brain white matter tractography. In Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings. 2017. p. 425-435. (Communications in Computer and Information Science). Epub 2017 Jun 22. doi: 10.1007/978-3-319-60964-5_37

Improved reference tracts for unsupervised brain white matter tractography

Abstract / Description of output

Publication series

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Projects

RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.

Cite this