Generative diffeomorphic atlas construction from brain and spinal cord MRI data

Claudia Blaiotta, Patrick Freund, M. Jorge Cardoso, John Ashburner

Research output: Contribution to journalArticlepeer-review

136 Downloads (Pure)

Abstract

In this paper we will focus on the potential and on the challenges associated with the development of an integrated brain and spinal cord modelling framework for processing MR neuroimaging data. The aim of the work is to explore how a hierarchical generative model of imaging data, which captures simultaneously the distribution of signal intensities and the variability of anatomical shapes across a large population of subjects, can serve to quantitatively investigate, in vivo, the morphology of the central nervous system (CNS). In fact, the generality of the proposed Bayesian approach, which extends the hierarchical structure of the segmentation method implemented in the SPM software, allows processing simultaneously information relative to different compartments of the CNS, namely the brain and the spinal cord, without having to resort to organ specific solutions (e.g. tools optimised only for the brain, or only for the spinal cord), which are inevitably harder to integrate and generalise.
Original languageEnglish
Journal arXiv
Publication statusPublished - 5 Jul 2017

Keywords

  • cs.CV

Fingerprint

Dive into the research topics of 'Generative diffeomorphic atlas construction from brain and spinal cord MRI data'. Together they form a unique fingerprint.

Cite this