English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

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

Dinse, J., Wähnert, M., Tardif, C., Schäfer, A., Geyer, S., Turner, R., et al. (2013). A histology-based model of quantitative T1 contrast for in-vivo cortical parcellation of high-resolution 7 Tesla brain MR images. In K. Mori, I. Sakuma, Y. Sato, C. Barillot, & N. Navab (Eds.), Medical image computing and computer-assisted intervention – MICCAI 2013 (pp. 51-58). Berlin: Springer. doi:10.1007/978-3-642-40763-5_7.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-7738-7 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-CDC4-0
Genre: Conference Paper

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Dinse, Juliane1, 2, Author              
Wähnert, Miriam1, Author              
Tardif, Christine1, Author              
Schäfer, Andreas1, Author              
Geyer, Stefan1, Author              
Turner, Robert1, Author              
Bazin, Pierre-Louis1, Author              
Affiliations:
1Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
2Faculty of Computer Science, Otto von Guericke University Magdeburg, Germany, ou_persistent22              

Content

show
hide
Free keywords: Myeloarchitecture; Cytoarchitetcure; Ultra-high resolution MRI; Cortical parcellation
 Abstract: 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.

Details

show
hide
Language(s): eng - English
 Dates: 2013-05-2020132013
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/978-3-642-40763-5_7
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Medical image computing and computer-assisted intervention – MICCAI 2013
Source Genre: Proceedings
 Creator(s):
Mori, Kensaku, Editor
Sakuma, Ichiro, Editor
Sato, Yoshinobu, Editor
Barillot, Christian, Editor
Navab, Nassir, Editor
Affiliations:
-
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 51 - 58 Identifier: ISBN: 978-3-642-40762-8