A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images

Akshay Sadananda Uppinakudru Pai; Stefan Horst Sommer; Lars Lau Raket; Line Kühnel; Sune Darkner; Lauge Sørensen; Mads Nielsen

doi:10.1007/978-3-319-61188-4_14

A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images

Akshay Sadananda Uppinakudru Pai, Stefan Horst Sommer, Lars Lau Raket, Line Kühnel, Sune Darkner, Lauge Sørensen, Mads Nielsen

Datalogisk Institut

Abstract

Template estimation plays a crucial role in computational anatomy since it provides reference frames for performing statistical analysis of the underlying anatomical population variability. While building models for template estimation, variability in sites and image acquisition protocols need to be accounted for. To account for such variability, we propose a generative template estimation model that makes simultaneous inference of both bias fields in individual images, deformations for image registration, and variance hyperparameters. In contrast, existing maximum a posterori based methods need to rely on either bias-invariant similarity measures or robust image normalization. Results on synthetic and real brain MRI images demonstrate the capability of the model to capture heterogeneity in intensities and provide a reliable template estimation from registration.

Originalsprog	Engelsk
Titel	Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging : MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers
Redaktører	Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, M. Jorge Cardoso, Georg Langs, Bjoern Menze, Dmitris Metaxas, Albert Montillo, William M. Wells, Shaoting Zhang, Albert C. S. Chung, Mark Jenkinson, Annemie Ribbens
Antal sider	9
Forlag	Springer
Publikationsdato	2017
Sider	151-159
ISBN (Trykt)	978-3-319-61187-7
ISBN (Elektronisk)	978-3-319-61188-4
DOI	https://doi.org/10.1007/978-3-319-61188-4_14
Status	Udgivet - 2017
Begivenhed	3rd International Workshop on Bayesian and Graphical Models for Biomedical Imaging - Athen, Grækenland Varighed: 21 okt. 2016 → 21 okt. 2016 Konferencens nummer: 3

Workshop

Workshop	3rd International Workshop on Bayesian and Graphical Models for Biomedical Imaging
Nummer	3
Land/Område	Grækenland
By	Athen
Periode	21/10/2016 → 21/10/2016

Navn	Lecture notes in computer science
Vol/bind	10081
ISSN	0302-9743

Adgang til dokumentet

10.1007/978-3-319-61188-4_14

https://arxiv.org/pdf/1705.00432.pdf

Citationsformater

Pai, A. S. U., Sommer, S. H., Raket, L. L., Kühnel, L., Darkner, S., Sørensen, L., & Nielsen, M. (2017). A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images. I H. Müller, B. M. Kelm, T. Arbel, W. Cai, M. J. Cardoso, G. Langs, B. Menze, D. Metaxas, A. Montillo, W. M. Wells, S. Zhang, A. C. S. Chung, M. Jenkinson, & A. Ribbens (red.), Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers (s. 151-159). Springer. https://doi.org/10.1007/978-3-319-61188-4_14

A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images. / Pai, Akshay Sadananda Uppinakudru ; Sommer, Stefan Horst; Raket, Lars Lau et al.
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers. red. / Henning Müller; B. Michael Kelm; Tal Arbel; Weidong Cai; M. Jorge Cardoso; Georg Langs; Bjoern Menze; Dmitris Metaxas; Albert Montillo; William M. Wells; Shaoting Zhang; Albert C. S. Chung; Mark Jenkinson; Annemie Ribbens. Springer, 2017. s. 151-159 (Lecture notes in computer science, Bind 10081).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Pai, ASU , Sommer, SH, Raket, LL, Kühnel, L, Darkner, S , Sørensen, L & Nielsen, M 2017, A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images. i H Müller, BM Kelm, T Arbel, W Cai, MJ Cardoso, G Langs, B Menze, D Metaxas, A Montillo, WM Wells, S Zhang, ACS Chung, M Jenkinson & A Ribbens (red), Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers. Springer, Lecture notes in computer science, bind 10081, s. 151-159, 3rd International Workshop on Bayesian and Graphical Models for Biomedical Imaging, Athen, Grækenland, 21/10/2016. https://doi.org/10.1007/978-3-319-61188-4_14

Pai ASU , Sommer SH, Raket LL, Kühnel L, Darkner S , Sørensen L et al. A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images. I Müller H, Kelm BM, Arbel T, Cai W, Cardoso MJ, Langs G, Menze B, Metaxas D, Montillo A, Wells WM, Zhang S, Chung ACS, Jenkinson M, Ribbens A, red., Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers. Springer. 2017. s. 151-159. (Lecture notes in computer science, Bind 10081). doi: 10.1007/978-3-319-61188-4_14

Pai, Akshay Sadananda Uppinakudru ; Sommer, Stefan Horst ; Raket, Lars Lau et al. / A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images. Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers. red. / Henning Müller ; B. Michael Kelm ; Tal Arbel ; Weidong Cai ; M. Jorge Cardoso ; Georg Langs ; Bjoern Menze ; Dmitris Metaxas ; Albert Montillo ; William M. Wells ; Shaoting Zhang ; Albert C. S. Chung ; Mark Jenkinson ; Annemie Ribbens. Springer, 2017. s. 151-159 (Lecture notes in computer science, Bind 10081).

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abstract = "Template estimation plays a crucial role in computational anatomy since it provides reference frames for performing statistical analysis of the underlying anatomical population variability. While building models for template estimation, variability in sites and image acquisition protocols need to be accounted for. To account for such variability, we propose a generative template estimation model that makes simultaneous inference of both bias fields in individual images, deformations for image registration, and variance hyperparameters. In contrast, existing maximum a posterori based methods need to rely on either bias-invariant similarity measures or robust image normalization. Results on synthetic and real brain MRI images demonstrate the capability of the model to capture heterogeneity in intensities and provide a reliable template estimation from registration.",

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AU - Pai, Akshay Sadananda Uppinakudru

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AU - Kühnel, Line

AU - Darkner, Sune

AU - Sørensen, Lauge

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AB - Template estimation plays a crucial role in computational anatomy since it provides reference frames for performing statistical analysis of the underlying anatomical population variability. While building models for template estimation, variability in sites and image acquisition protocols need to be accounted for. To account for such variability, we propose a generative template estimation model that makes simultaneous inference of both bias fields in individual images, deformations for image registration, and variance hyperparameters. In contrast, existing maximum a posterori based methods need to rely on either bias-invariant similarity measures or robust image normalization. Results on synthetic and real brain MRI images demonstrate the capability of the model to capture heterogeneity in intensities and provide a reliable template estimation from registration.

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A2 - Langs, Georg

A2 - Menze, Bjoern

A2 - Metaxas, Dmitris

A2 - Montillo, Albert

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A2 - Zhang, Shaoting

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A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images

Abstract

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