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Detecting Alzheimer’s disease by morphological MRI using hippocampal grading and cortical thickness

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Simon Fristed Eskildsen
  • Pierrick Coupé, Laboratoire Bordelais de Recherche en Informatique, Unité Mixte de Recherche CNRS (UMR 5800), PICTURA Group, Bordeaux, France., France
  • Vladimir Fonov, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Canada
  • D. Louis Collins, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Canada
Structural MRI is an important imaging biomarker in Alzheimer’s disease as the cerebral atrophy has been shown to closely correlate with cogni-tive symptoms. Recognizing this, numerous methods have been developed for quantifying the disease related atrophy from MRI over the past decades. Special effort has been dedicated to separate AD related modifications from normal ag-ing for the purpose of early detection and prediction. Several groups have re-ported promising results using automatic methods; however, it is very difficult to compare these methods due to varying cohorts and different validation frameworks. To address this issue, the public challenge on Computer-Aided Di-agnosis of Dementia based on structural MRI data (CADDementia) was pro-posed. The challenge calls for accurate classification of 354 MRI scans collect-ed among AD patients, subjects with mild cognitive impairment and cognitively normal control. The true diagnosis is hidden from the participating groups, thus making the validation truly objective. This paper describes our proposed meth-od to automatically classify the challenge data along with a validation on 30 scans with known diagnosis also provided for the challenge.
Original languageEnglish
Title of host publicationChallenge on Computer-Aided Diagnosis of Dementia based on structural MRI data
EditorsEsther Bron, Marion Smits, John van Swieten, Wiro Niessen, Stefan Klein
Number of pages10
Publication year18 Sep 2014
Pages38-47
Publication statusPublished - 18 Sep 2014
EventMedical Image Computing and Computer Assisted Intervention conference 2014 - Boston, United States
Duration: 14 Sep 201418 Feb 2015
Conference number: 2014

Conference

ConferenceMedical Image Computing and Computer Assisted Intervention conference 2014
Nummer2014
LandUnited States
ByBoston
Periode14/09/201418/02/2015

    Research areas

  • MRI, Alzheimer, Prediction, Classification, Machine learning, Image processing

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