Scholars@Duke publication: A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images.

A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images.

Publication , Conference

Dinse, J; Waehnert, M; Tardif, CL; Schäfer, A; Geyer, S; Turner, R; Bazin, P-L

Published in: Med Image Comput Comput Assist Interv

2013

A conclusive mapping of myeloarchitecture (myelin patterns) onto the cortical sheet and, thus, a corresponding mapping to cytoarchitecture (cell configuration) does not exist today. In this paper we present a generative model which can predict, on the basis of known cytoarchitecture, myeloarchitecture in different primary and non-primary cortical areas, resulting in simulated in-vivo quantitative T1 maps. The predicted patterns can be used in brain parcellation. Our model is validated using a similarity distance metric which enables quantitative comparison of the results with empirical data measured using MRI. The work presented may provide new perspectives for this line of research, both in imaging and in modelling the relationship with myelo- and cytoarchitecture, thus leading the way towards in-vivo histology using MRI.

Duke Scholars

Author Robert Turner II Population Health Sciences

Published In

Med Image Comput Comput Assist Interv

DOI

10.1007/978-3-642-40763-5_7

Publication Date

2013

Volume

Issue

Pt 2

Start / End Page

51 / 58

Location

Germany

Related Subject Headings

Sensitivity and Specificity
Reproducibility of Results
Pattern Recognition, Automated
Models, Statistical
Models, Neurological
Models, Biological
Models, Anatomic
Magnetic Resonance Imaging
Imaging, Three-Dimensional
Image Interpretation, Computer-Assisted

Citation

APA

Chicago

ICMJE

MLA

NLM

Dinse, J., Waehnert, M., Tardif, C. L., Schäfer, A., Geyer, S., Turner, R., & Bazin, P.-L. (2013). A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images. In Med Image Comput Comput Assist Interv (Vol. 16, pp. 51–58). Germany. https://doi.org/10.1007/978-3-642-40763-5_7

Dinse, Juliane, Miriam Waehnert, Christine Lucas Tardif, Andreas Schäfer, Stefan Geyer, Robert Turner, and Pierre-Louis Bazin. “A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images.” In Med Image Comput Comput Assist Interv, 16:51–58, 2013. https://doi.org/10.1007/978-3-642-40763-5_7.

Dinse J, Waehnert M, Tardif CL, Schäfer A, Geyer S, Turner R, et al. A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images. In: Med Image Comput Comput Assist Interv. 2013. p. 51–8.

Dinse, Juliane, et al. “A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images.” Med Image Comput Comput Assist Interv, vol. 16, no. Pt 2, 2013, pp. 51–58. Pubmed, doi:10.1007/978-3-642-40763-5_7.

Dinse J, Waehnert M, Tardif CL, Schäfer A, Geyer S, Turner R, Bazin P-L. A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images. Med Image Comput Comput Assist Interv. 2013. p. 51–58.

Published In

Med Image Comput Comput Assist Interv

DOI

10.1007/978-3-642-40763-5_7

Publication Date

2013

Volume

Issue

Pt 2

Start / End Page

51 / 58

Location

Germany

Related Subject Headings

Sensitivity and Specificity
Reproducibility of Results
Pattern Recognition, Automated
Models, Statistical
Models, Neurological
Models, Biological
Models, Anatomic
Magnetic Resonance Imaging
Imaging, Three-Dimensional
Image Interpretation, Computer-Assisted