Key points are not available for this paper at this time.
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.
Building similarity graph...
Analyzing shared references across papers
Loading...
Arno Klein
Child Mind Institute
Jason A. Tourville
Boston University
Frontiers in Neuroscience
SHILAP Revista de lepidopterología
Columbia University
Boston University
Stony Brook University
Building similarity graph...
Analyzing shared references across papers
Loading...
Klein et al. (Sun,) studied this question.
synapsesocial.com/papers/69d9644f00ab073a278365de — DOI: https://doi.org/10.3389/fnins.2012.00171