Warping an atlas derived from serial histology to 5 high-resolution MRIs.
Title | Warping an atlas derived from serial histology to 5 high-resolution MRIs. |
Publication Type | Journal Article |
Year of Publication | 2018 |
Authors | Tullo S, Devenyi GA, Patel R, Park MTae M, D Collins L, Chakravarty MM |
Journal | Sci Data |
Volume | 5 |
Pagination | 180107 |
Date Published | 2018 Jun 19 |
ISSN | 2052-4463 |
Abstract | Previous work from our group demonstrated the use of multiple input atlases to a modified multi-atlas framework (MAGeT-Brain) to improve subject-based segmentation accuracy. Currently, segmentation of the striatum, globus pallidus and thalamus are generated from a single high-resolution and -contrast MRI atlas derived from annotated serial histological sections. Here, we warp this atlas to five high-resolution MRI templates to create five de novo atlases. The overall goal of this work is to use these newly warped atlases as input to MAGeT-Brain in an effort to consolidate and improve the workflow presented in previous manuscripts from our group, allowing for simultaneous multi-structure segmentation. The work presented details the methodology used for the creation of the atlases using a technique previously proposed, where atlas labels are modified to mimic the intensity and contrast profile of MRI to facilitate atlas-to-template nonlinear transformation estimation. Dice's Kappa metric was used to demonstrate high quality registration and segmentation accuracy of the atlases. The final atlases are available at https://github.com/CobraLab/atlases/tree/master/5-atlas-subcortical. |
DOI | 10.1038/sdata.2018.107 |
Alternate Journal | Sci Data |
PubMed ID | 29917012 |