Projects:RegistrationLibrary:RegLib C26
From NAMIC Wiki
Home < Projects:RegistrationLibrary:RegLib C26
Back to ARRA main page
Back to Registration main page
Back to Registration Use-case Inventory
Slicer Registration Library Exampe #26: Fusion of WM parcellation atlas with anatomic brain atlas
Objective / Background
This is an example of inter-subject registration. The structures of interest are WM parcellations from the JHU-MNI atlas (see acknowledgments).
Keywords
MRI, brain, head, inter-subject, atlas to atlas, WM parcellation
Input Data
- moving: b0 image of JHU_MNI white matter atlas. Called A2_gray
- tag: WM parcellation labelmap A2_label
Methods
Registration Results
Download
- download SPL atlas (MRI T1+T2, labelmaps , colormap file with label names), zip file 126 MB)
- download JHU-MNI Mori / "Eve" Atlas (MRI T1+T2, 3 labelmaps with WM parcellation, 3 Slicer LUT text files with label names + Colors), zip file 28 MB)
- download Label & Color LUT (diffferent formats of LUT text files with label names, colors, comments ), zip file 50 kB)
- Mori Atlas page on Slicer Wiki
- LUT converter website
- Link to User Guide: How to Load/Save Registration Parameter Presets
Discussion: Registration Challenges
- the two atlases represent different anatomies and hence some residual misalignment is inevitable
- the two labelmaps have different resolutions and different smoothness of structure outlines. Some need filtering to remove spurious surface details that would distract the registration algorithm
Discussion: Key Strategies
Acknowledgments
- dataset obtained from MRI studio with permission from the Johns Hopkins University School of Medicine, Department of Radiology Center for Brain Imaging Science. Our thanks to Drs. Susumo Mori, Kenichi Oishi and Andreia Faria .
- For details please see:
- Mori S., Oishi K., Jiang H, Jiang L., Li X., Akhter K., Hua K., Faria AV., Mahmod A., Woods R., Toga WA., Pike B, Rosa Neto P, Evans A, Zhang J, Huang H, Miller MI, van Zijl, PCM, Mazziotta, J, "Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template", Neuroimage. 2008 Apr 1;40(2):570-82.
- Oishi K, Zilles K, Amunts K, Faria A, Jiang H, Li X, Akhter K, Hua K, Woods R, Toga AW, Pike GB, Posa-Neto P, Evans A, Zhang J, Huang H, Mikker MI, van Zijl PCM, Mazziotta J, Mori S, "Human brain white matter atlas: identification and assignment of common anatomical structures in superficial white matter." Neuroimage. 2008 Nov 15;43(3):447-57.
- Oishi K, Faria A, Jiang H, Li X, Akhter K, Zhang J, Hsu J, Miller MI, van Zijl PCM, Albert M, Lyketsos CG, Woods R, Toga AW, Pike GB, Rosa-Neto P, Evans A, Mazziotta J, Mori S "Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimers' disease participants", Neuroimage. 2009 Jun;46(2):486-99.
"We are pleased to make our white matter atlas available. The JHU-MNI-ss atlas, which is often called "Eve Atlas", is based on a single-subject data as described in Oishi et al, 2009. There are co-registered T1 (MPRAGE), T2, and DTI images as well as white matter parcellation map (WMPM). Once the image of interest is normalized to this atlas coordinate, the WMPM (which also includes gray matter structures) can be superimposed for anatomical definition (e.g. which structure is affected by a lesion or where exactly is the fMRI activation site) or automated segmentation. All images have 181x217x181 / 1x1x1 mm dimensions."