Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2012Cortical surface mapping using topology correction, partial flattening and 3D shape context-based non-rigid registration for use in quantifying atrophy in Alzheimer’s diseasecitations

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Chart of shared publication
Villemagne, Victor
1 / 2 shared
Salvado, Olivier
1 / 2 shared
Xiao, Di
1 / 2 shared
Masters, Colin
1 / 2 shared
Martins, Ralph
1 / 2 shared
Chetelat, Gael
1 / 1 shared
Rueda, Andrea
1 / 1 shared
Szoeke, Cassandra
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Barra, Vincent
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Acosta, Oscar
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Ellis, Kathryn
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Fripp, Jurgen
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Rowe, Chris
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Gris, Florence
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Bonner, Erik
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Raniga, Parnesh
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Ames, David
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Chart of publication period
2012

Co-Authors (by relevance)

  • Villemagne, Victor
  • Salvado, Olivier
  • Xiao, Di
  • Masters, Colin
  • Martins, Ralph
  • Chetelat, Gael
  • Rueda, Andrea
  • Szoeke, Cassandra
  • Barra, Vincent
  • Acosta, Oscar
  • Ellis, Kathryn
  • Fripp, Jurgen
  • Rowe, Chris
  • Gris, Florence
  • Bonner, Erik
  • Raniga, Parnesh
  • Ames, David
OrganizationsLocationPeople

article

Cortical surface mapping using topology correction, partial flattening and 3D shape context-based non-rigid registration for use in quantifying atrophy in Alzheimer’s disease

  • Villemagne, Victor
  • Salvado, Olivier
  • Xiao, Di
  • Masters, Colin
  • Martins, Ralph
  • Chetelat, Gael
  • Rueda, Andrea
  • Favreau, Jean-Marie
  • Szoeke, Cassandra
  • Barra, Vincent
  • Acosta, Oscar
  • Ellis, Kathryn
  • Fripp, Jurgen
  • Rowe, Chris
  • Gris, Florence
  • Bonner, Erik
  • Raniga, Parnesh
  • Ames, David
Abstract

Magnetic resonance (MR) provides a non-invasive imaging technique to investigate changes in the brain resulting from normal aging or neurodegenerative disorders such as Alzheimer's disease (AD). Performing accurate analysis of brain imaging data for population studies is challenging because of the interindividual anatomical variability. In this paper we present a newly developed surface-based processing pipeline that allows accurate vertice-wise statistical comparisons of brain modifications, such as cortical thickness (CTE). The brain is first segmented into the three main brain tissue types: white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF), CTEis computed after which a topology corrected mesh is generated. Partial inflation and non rigid registration to a common space using shape context are then performed. Each of the steps was validated using MR images from the OASIS database. We also applied the pipeline to a sample of individuals from the AIBL study on AD. Results were compared with Freesurfer (FS). For a population of 50 individuals we found a strong correlation between CTE computed with FS in all the regions of the brain (average=0.62 left and=0.64 right hemispheres). We finally computed changes in CTE in 32 AD patients and 81 healthy elderly individuals (HC). Significant differences were found in regions known to be affected in AD (temporal lobe, hippocampus, cingulate). We demonstrated the validitity of the method for use in clinical studies which provides an alternative to well established technniques and allows the comparison between different imaging biomarkers for the study of neurodegenerative diseases.

Topics
  • impedance spectroscopy
  • surface
  • aging
  • aging