Training labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol.

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dc.contributor.authorBoccardi, Marina
dc.contributor.authorBocchetta, Martina
dc.contributor.authorMorency, Félix C
dc.contributor.authorCollins, D Louis
dc.contributor.authorNishikawa, Masami
dc.contributor.authorGanzola, Rossana
dc.contributor.authorGrothe, Michel J
dc.contributor.authorWolf, Dominik
dc.contributor.authorRedolfi, Alberto
dc.contributor.authorPievani, Michela
dc.contributor.authorAntelmi, Luigi
dc.contributor.authorFellgiebel, Andreas
dc.contributor.authorMatsuda, Hiroshi
dc.contributor.authorTeipel, Stefan
dc.contributor.authorDuchesne, Simon
dc.contributor.authorJack, Clifford R
dc.contributor.authorFrisoni, Giovanni B
dc.contributor.author,
dc.date.accessioned2020-02-10T17:49:06Z
dc.date.available2020-02-10T17:49:06Z
dc.date.issued2015-01-24
dc.description.abstractThe European Alzheimer s Disease Consortium and Alzheimer s Disease Neuroimaging Initiative ADNI Harmonized Protocol HarP is a Delphi definition of manual hippocampal segmentation from magnetic resonance imaging MRI that can be used as the standard of truth to train new tracers and to validate automated segmentation algorithms Training requires large and representative data sets of segmented hippocampi This work aims to produce a set of HarP labels for the proper training and certification of tracers and algorithms
dc.identifier.urihttp://dx.doi.org/10.1016/j.jalz.2014.12.002
dc.identifier.urihttps://lib.digitalsquare.io/xmlui/handle/123456789/27953
dc.relation.uriAlzheimer's And dementia : the journal of the Alzheimer's Association
dc.titleTraining labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol.en
dcterms.abstractThe European Alzheimer s Disease Consortium and Alzheimer s Disease Neuroimaging Initiative ADNI Harmonized Protocol HarP is a Delphi definition of manual hippocampal segmentation from magnetic resonance imaging MRI that can be used as the standard of truth to train new tracers and to validate automated segmentation algorithms Training requires large and representative data sets of segmented hippocampi This work aims to produce a set of HarP labels for the proper training and certification of tracers and algorithms
dcterms.contributorBoccardi, Marina
dcterms.contributorBocchetta, Martina
dcterms.contributorMorency, Félix C
dcterms.contributorCollins, D Louis
dcterms.contributorNishikawa, Masami
dcterms.contributorGanzola, Rossana
dcterms.contributorGrothe, Michel J
dcterms.contributorWolf, Dominik
dcterms.contributorRedolfi, Alberto
dcterms.contributorPievani, Michela
dcterms.contributorAntelmi, Luigi
dcterms.contributorFellgiebel, Andreas
dcterms.contributorMatsuda, Hiroshi
dcterms.contributorTeipel, Stefan
dcterms.contributorDuchesne, Simon
dcterms.contributorJack, Clifford R
dcterms.contributorFrisoni, Giovanni B
dcterms.contributor,
dcterms.identifierhttp://dx.doi.org/10.1016/j.jalz.2014.12.002
dcterms.relationAlzheimer's And dementia : the journal of the Alzheimer's Association
dcterms.titleTraining labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol.en
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