Title |
101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol
|
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Published in |
Frontiers in Neuroscience, January 2012
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DOI | 10.3389/fnins.2012.00171 |
Pubmed ID | |
Authors |
Arno Klein, Jason Tourville |
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. |
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United States | 3 | 13% |
Australia | 1 | 4% |
Ireland | 1 | 4% |
Turkey | 1 | 4% |
Netherlands | 1 | 4% |
Norway | 1 | 4% |
Unknown | 10 | 43% |
Demographic breakdown
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---|---|---|
Members of the public | 15 | 65% |
Scientists | 6 | 26% |
Practitioners (doctors, other healthcare professionals) | 2 | 9% |
Mendeley readers
Geographical breakdown
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Germany | 5 | <1% |
Canada | 4 | <1% |
United Kingdom | 3 | <1% |
China | 2 | <1% |
Cuba | 2 | <1% |
Norway | 1 | <1% |
Brazil | 1 | <1% |
France | 1 | <1% |
Other | 6 | <1% |
Unknown | 646 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 159 | 23% |
Researcher | 129 | 19% |
Student > Master | 75 | 11% |
Other | 36 | 5% |
Student > Doctoral Student | 35 | 5% |
Other | 120 | 18% |
Unknown | 123 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 148 | 22% |
Medicine and Dentistry | 80 | 12% |
Psychology | 61 | 9% |
Engineering | 59 | 9% |
Computer Science | 55 | 8% |
Other | 96 | 14% |
Unknown | 178 | 26% |