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A validation dataset for Macaque brain MRI segmentation
- Source :
- Data in Brief, Vol 16, Iss, Pp 37-42 (2018), Data in Brief, Data in Brief, Elsevier, 2018, 16, pp.37-42. ⟨10.1016/j.dib.2017.11.008⟩, Data in Brief, 2018, 16, pp.37-42. ⟨10.1016/j.dib.2017.11.008⟩
- Publication Year :
- 2018
- Publisher :
- Elsevier, 2018.
-
Abstract
- International audience; Validation data for segmentation algorithms dedicated to preclinical images is fiercely lacking, especially when compared to the large number of databases of Human brain images and segmentations available to the academic community. Not only is such data essential for validating methods, it is also needed for objectively comparing concurrent algorithms and detect promising paths, as segmentation challenges have shown for clinical images.The dataset we present here is a first step in this direction. It comprises 10 T2-weighted MRIs of healthy adult macaque brains, acquired on a 7 T magnet, along with corresponding manual segmentations into 17 brain anatomic labelled regions spread over 5 hierarchical levels based on a previously published macaque atlas (Calabrese et al., 2015) [1].By giving access to this unique dataset, we hope to provide a reference needed by the non-human primate imaging community. This dataset was used in an article presenting a new primate brain morphology analysis pipeline, Primatologist (Balbastre et al., 2017) [2]. Data is available through a NITRC repository (https://www.nitrc.org/projects/mircen_macset).
- Subjects :
- Computer science
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
computer.software_genre
lcsh:Computer applications to medicine. Medical informatics
Macaque
050105 experimental psychology
03 medical and health sciences
0302 clinical medicine
biology.animal
Brain mri
0501 psychology and cognitive sciences
Segmentation
lcsh:Science (General)
Multidisciplinary
biology
business.industry
05 social sciences
Brain morphometry
Pattern recognition
Academic community
lcsh:R858-859.7
[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
Artificial intelligence
Data mining
business
computer
030217 neurology & neurosurgery
Neuroscience
lcsh:Q1-390
Subjects
Details
- Language :
- English
- ISSN :
- 23523409
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- Data in Brief
- Accession number :
- edsair.doi.dedup.....75df516a9acdd18f446aea3d74125812
- Full Text :
- https://doi.org/10.1016/j.dib.2017.11.008⟩