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101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol
Arno Klein, Jason Tourville
Frontiers in Neuroscience · 2012
doi:10.3389/fnins.2012.00171 (opens in a new tab)
Abstract
We introduce the Mindboggle-101 dataset, the largest and most complete set of free, publicly accessible, manually labeled human brain images. To manually label the macroscopic anatomy in magnetic resonance images of 101 healthy participants, we created a new cortical labeling protocol that relies on robust anatomical landmarks and minimal manual edits after initialization with automated labels. The "Desikan-Killiany-Tourville" (DKT) protocol is intended to improve the ease, consistency, and accuracy of labeling human cortical areas. Given how difficult it is to label brains, the Mindboggle-101 dataset is intended to serve as brain atlases for use in labeling other brains, as a normative dataset to establish morphometric variation in a healthy population for comparison against clinical populations, and contribute to the development, training, testing, and evaluation of automated registration and labeling algorithms. To this end, we also introduce benchmarks for the evaluation of such algorithms by comparing our manual labels with labels automatically generated by probabilistic and multi-atlas registration-based approaches. All data and related software and updated information are available on the http://mindboggle.info/data website.
References 36
- 1.
Aljabar P. Heckemann R. A. Hammers A. Hajnal J. V. Rueckert D. (2009 ). Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy. Neuroimage 46, 726–738
Not in our library10.1016/j.neuroimage.2009.02.018 (opens in a new tab)
- 2.
Avants B. B. Yushkevich P. Pluta J. Minkoff D. Korczykowski M. Detre J. (2010 ). The optimal template effect in hippocampus studies of diseased populations. Neuroimage 49, 2457–2466
Not in our library10.1016/j.neuroimage.2009.09.062 (opens in a new tab)
- 3.
Bilder R. M. Toga A. W. Mirza M. Shattuck D. W. Adisetiyo V. Salamon G. (2008 ). Construction of a 3D probabilistic atlas of human cortical structures. Neuroimage 39, 1064–1080
Not in our library10.1016/j.neuroimage.2007.09.031 (opens in a new tab)
- 4.
- 5.
Cachia A. Paillère-Martinot M.-L. Galinowski A. Januel D. de Beaurepaire R. Bellivier F. (2008 ). Cortical folding abnormalities in schizophrenia patients with resistant auditory hallucinations. Neuroimage 39, 927–935
Not in our library10.1016/j.neuroimage.2007.08.049 (opens in a new tab)
- 6.
Caviness V. S. Meyer J. Makris N. Kennedy D. N. (1996 ). MRI-based topographic parcellation of human neocortex: an anatomically specified method with estimate of reliability. J. Cogn. Neurosci. 8, 566–587
Not in our library10.1162/jocn.1996.8.6.566 (opens in a new tab)
- 7.
Cointepas Y. Mangin J.-F. Garnero L. Poline J.-B. Benali H. (2001 ). BrainVISA: software platform for visualization and analysis of multi-modality brain data. Hum. Brain Mapp. 13(Suppl.), 98
Not in our library
- 8.
Crespo-Facorro B. Kim J.-J. Andreasen N. C. Spinks R. O’Leary D. S. Bockholt H. J. (2000 ). Cerebral cortex: a topographic segmentation method using magnetic resonance imaging. Psychiatry Res. 100, 97–126
Not in our library10.1016/s0925-4927(00)00072-x (opens in a new tab)
- 9.
Dale A. M. Fischl B. Sereno M. I. (1999 ). Cortical surface-based analysis. I: segmentation and surface reconstruction. Neuroimage 9, 179–194
Not in our library10.1006/nimg.1998.0395 (opens in a new tab)
- 10.
Damasio H. (2005 ). Human Brain Anatomy in Computerized Images, 2nd Edn New York: Oxford University Press
Not in our library
- 11.
Delcroix N. Tzourio-Mazoyer N. Landeau B. Papathanassiou D. Crivello F. Mazoyer B. (2002 ). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15, 273–289
Not in our library10.1006/nimg.2001.0978 (opens in a new tab)
- 12.
Desikan R. S. Segonne F. Fischl B. Quinn B. T. Dickerson B. C. Blacker D. (2006 ). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 3, 968–980
Not in our library10.1016/j.neuroimage.2006.01.021 (opens in a new tab)
- 13.
Destrieux C. Fischl B. Dale A. Halgren E. (2010 ). Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage 53, 1–15
Not in our library10.1016/j.neuroimage.2010.06.010 (opens in a new tab)
- 14.
Duvernoy H. M. (1999 ). The Human Brain: Surface, Blood Supply, and Three Dimensional Anatomy. New York: Springer-Verlag Wien
Not in our library
- 15.
Fischl B. Liu A. Dale A. M. (2001 ). Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Trans. Med. Imaging 20, 70–80
Not in our library10.1109/42.906426 (opens in a new tab)
- 16.
Fischl B. Salat D. H. Busa E. Dale A. M. Klaveness S. Haselgrove C. (2002 ). Whole brain segmentation: neurotechnique automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341–355
Not in our library10.1016/s0896-6273(02)00569-x (opens in a new tab)
- 17.
Fischl B. Sereno M. I. Dale A. M. (1999 ). Cortical surface-based analysis II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 9, 179–194
Not in our library10.1006/nimg.1998.0396 (opens in a new tab)
- 18.
- 19.
Heckemann R. A. Hajnal J. V. Aljabar P. Rueckert D. Hammers A. (2006 ). Automatic anatomical brain {MRI} segmentation combining label propagation and decision fusion. Neuroimage 33, 115–126
Not in our library10.1016/j.neuroimage.2006.05.061 (opens in a new tab)
- 20.
Holmes C. J. Hoge R. Collins L. Woods R. Toga A. W. Evans A. C. (1998 ). Enhancement of MR images using registration for signal averaging. J. Comput. Assist. Tomogr. 22, 324–333
Not in our library10.1097/00004728-199803000-00032 (opens in a new tab)
- 21.
Kempton M. J. Salvador Z. Munafò M. R. Geddes J. R. Simmons A. Frangou S. (2011 ). Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder. Arch. Gen. Psychiatry 68, 675–690
Not in our library10.1001/archgenpsychiatry.2011.60 (opens in a new tab)
- 22.
Klein A. Andersson J. Ardekani B. A. Ashburner J. Avants B. Chiang M.-C. (2009 ). Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. Neuroimage 46, 786–802
Not in our library10.1016/j.neuroimage.2008.12.037 (opens in a new tab)
- 23.
Klein A. Dal Canton T. Ghosh S. S. Landman B. Lee J. Worth A. (2010a ). Open labels: online feedback for a public resource of manually labeled brain images. 16th Annual Meeting for the Organization of Human Brain Mapping, Barcelona
Not in our library
- 24.
Klein A. Ghosh S. S. Avants B. Yeo B. T. T. Fischl B. Ardekani B. (2010b ). Evaluation of volume-based and surface-based brain image registration methods. Neuroimage 51, 214–220
Not in our library10.1016/j.neuroimage.2010.01.091 (opens in a new tab)
- 25.
Klein A. Hirsch J. (2005 ). Mindboggle: a scatterbrained approach to automate brain labeling. Neuroimage 24, 261–280
Not in our library10.1016/j.neuroimage.2004.09.016 (opens in a new tab)
- 26.
Klein A. Mensh B. Ghosh S. Tourville J. Hirsch J. (2005 ). Mindboggle: automated brain labeling with multiple atlases. BMC Med. Imaging 5:7
Not in our library10.1186/1471-2342-5-7 (opens in a new tab)
- 27.
Landman B. A. Huang A. J. Gifford A. Vikram D. S. Lim I. A. L. Farrell J. A. D. (2011 ). Multi-parametric neuroimaging reproducibility: a 3-T resource study. Neuroimage 54, 2854–2866
Not in our library10.1016/j.neuroimage.2010.11.047 (opens in a new tab)
- 28.
Lohmann G. von Cramon D. Y. (2000 ). Automatic labelling of the human cortical surface using sulcal basins. Med. Image Anal. 4, 179–188
Not in our library10.1016/s1361-8415(00)00024-4 (opens in a new tab)
- 29.
Mai J. Paxinos G. Voss T. (2008 ). Atlas of the Human Brain. New York: Elsevier
Not in our library
- 30.
Mangin J.-F. Jouvent E. Cachia A. (2010 ). In-vivo measurement of cortical morphology: means and meanings. Curr. Opin. Neurol. 23, 359–367
Not in our library10.1097/wco.0b013e32833a0afc (opens in a new tab)
- 31.
Marcus D. S. Wang T. H. Parker J. Csernansky J. G. Morris J. C. Buckner R. L. (2007 ). Open access series of imaging studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. J. Cogn. Neurosci. 19, 1498–1507
Not in our library10.1162/jocn.2007.19.9.1498 (opens in a new tab)
- 32.
Morgan V. L. Mishra A. Newton A. T. Gore J. C. Ding Z. (2009 ). Integrating functional and diffusion magnetic resonance imaging for analysis of structure–function relationship in the human language network. PLoS ONE 4:e6660
Not in our library10.1371/journal.pone.0006660 (opens in a new tab)
- 33.
Ono M. Kubik S. Abernathy C. D. (1990 ). Atlas of the Cerebral Sulci. Stuttgart: Georg Thieme Verlag
Not in our library
- 34.
Penttilä J. Cachia A. Martinot J.-L. Ringuenet D. Wessa M. Houenou J. (2009 ). Cortical folding difference between patients with early-onset and patients with intermediate-onset bipolar disorder. Bipolar Disord. 11, 361–370
Not in our library10.1111/j.1399-5618.2009.00683.x (opens in a new tab)
- 35.
Petrides M. (2011 ). The Human Cerebral Cortex: An MRI Atlas of the Sulci and Gyri in MNI Stereotaxic Space. London: Academic Press
Not in our library
- 36.
S’egonne F. Salat D. H. Dale A. M. Destrieux C. Fischl B. van der Kouwe A. (2004 ). Automatically parcellating the human cerebral cortex. Cereb. Cortex 14, 11–22
Not in our library10.1093/cercor/bhg087 (opens in a new tab)
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