A data set of 41 subjects was obtained from Massachusetts General Hospital (MGH). This data is in freeSurfer format. The following subcortical structures have been segmented in this dataset: amygdala, caudate, hippocampus, pallidus, putamen, thallamus, ventricle. CIS used this dataset to generate a template (left and right) for each structure. The template was generated using large deformation diffeomorphic mapping (LDDMM) techniques. The template represents an average of the 41 subjects. In order to quantify shape change of subcortical structures with disease, subcortical surface data from Alzheimer's Disease Neuroimaging Initiative (ADNI) project, Open Access Series of Imaging Studies (OASIS) as well as freeSurfer data was compared to the templates. The surfaces are first aligned with the templates, then mapped to the templates using lddmm-surface, a CIS tool that maps surfaces to surfaces, using LDDMM methods.

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A postmortem brain was obtained from the Brain Resource Center, Department of Pathology, Johns Hopkins University. The brain tissues were fixed by 10% formaldehyde for more than two weeks. A section of the brain that included the amygdala, hippocampus and entorhinal cortex was sectioned from the right hemisphere of the brain, and scannned using a Bruker Biospec 11.7T scanner. The b0 modality scan was hand segmented to create amygdala, entorhinal cortex and hippocampus masks, inclduing subfields.

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A data set of 8 normal canine hearts was obtained from Drs. Patrick A. Helm and Raimond L. Winslow at the Center for Cardiovascular Bioinformatics and Modeling and Dr. Elliot McVeigh at the National Institute of Health. There are two kinds of data: geometry/scalar data and diffusion tensor data. We use the template estimation method developed at CIS to generate a geometry atlas based on geometry data. Then we use LDDMM to map the diffusion tensor data from the subject to the geometry atlas. Finally, the cardiac atlas will have both geometry and diffusion tensor data, which can be used to study shape variation in a population.

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An isotropic 7T MRI scan of resolution 0.8 mm was used to reconstruct high-field parcellation of the amygdala and hippocampus. The 7T subject is a 42 year old male who is healthy by self-report. The subject was scanned using a standard MPRAGE protocol in a Philips Achieva 7.0T scanner (TR =4.3 ms, TE=1.95ms, flip=7, FOV=220×220×180). The amygdala was subdivided into four nuclei: lateral, basolateral, basomedial and centromedial nuclei using definitions based on the Paxino Atlas of the Human Brain and illustrated in detail at Protocols. Similarly, the hippocampus was divided into CA1, CA2 and CA3, based on the same atlas.

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An isotropic, whole brain digital atlas with resolution 1 μm was used to reconstruct high-field parcellation of the thalamus (Ding S, Royall JJ, Sunkin SM, Ng L, Facer BA, Lesnar P, Guillozet‐Bongaarts A, McMurray B, Szafer A, Dolbeare TA, 2016: Comprehensive cellular‐resolution atlas of the adult human brain. Journal of Comparative Neurology., 524, 3127–3481). The atlas incorporates neuroimaging, high-resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and 1,356 large-format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. Anatomical delineation was done on a sub-set of the Nissl plates, with sampling intervals varying from 0.4 to 3.4 mm across the full anterior–posterior (A‐P) extent of the entire left hemisphere. Thus, 862 structures were delineated and digitally scanned. For the sub-field atlas, we segmented 27 sub-fields from the digital whole brain atlas. The slices were rigidly registered together to compensate for inter-slice misalignment. Since the slices were sampled at different intervals ranging from 0.4 to 3.4 mm, they were then interpolated and resliced using LDDMM to get uniformly spaced slices. Sub-field structures were then reconstructed in 3D using Restricted Delauney triangulation.

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