Published February 1, 2023
| Version 2.1.1
Software
Open
CABINET: BIDS-ified CABINET Application
Creators
-
Conan, Greg1
-
Houghton, Audrey1
-
Hendrickson, Timothy J.1
-
Alexopoulos, Dimitrios2
-
Goncalves, Mathias3
- Koirala, Sanju1
-
Latham, Aidan2
-
Lee, Erik1
-
Lundquist, Jacob1
-
Madison, Thomas J.1
-
Markiewicz, Christopher J.3
-
Moore, Lucille A.1
-
Moser, Julia1
-
Reiners, Paul1
-
Rueter, Amanda4
-
Fair, Damien A.1
-
Feczko, Eric1
- 1. Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN
- 2. Washington University, St. Louis, MO
- 3. Department of Psychology, Stanford University, Stanford, CA
- 4. University of Minnesota, Minneapolis, MN
Description
This BIDS App provides the utility of creating a nnU-Net anatomical MRI segmentation and mask with a infant brain trained model for the purposes of circumventing JLF within Nibabies.
This application utilities the following software: nvidia/pytorch:21.11-py3, nnU-Net, SynthSeg, FSL v6.0.5.1, ANTS v2.3.3, BIBSnet v1.0.0
Notes
Files
DCAN-Labs/CABINET-2.1.1.zip
Files
(52.1 kB)
Name | Size | Download all |
---|---|---|
md5:0f77f2187a784a818cf06d32f835c234
|
52.1 kB | Preview Download |
Additional details
Related works
- Is supplement to
- https://github.com/DCAN-Labs/CABINET/tree/2.1.1 (URL)
References
- Avants, Tustison, and Song. n.d. "Advanced Normalization Tools (ANTS)." The Insight Journal. https://scicomp.ethz.ch/public/manual/ants/2.x/ants2.pdf.
- Billot, Benjamin, Douglas N. Greve, Oula Puonti, Axel Thielscher, Koen Van Leemput, Bruce Fischl, Adrian V. Dalca, and Juan Eugenio Iglesias. 2021. "SynthSeg: Domain Randomisation for Segmentation of Brain Scans of Any Contrast and Resolution." arXiv [eess.IV]. arXiv. http://arxiv.org/abs/2107.09559.
- Howell, Brittany R., Martin A. Styner, Wei Gao, Pew-Thian Yap, Li Wang, Kristine Baluyot, Essa Yacoub, et al. 2019. "The UNC/UMN Baby Connectome Project (BCP): An Overview of the Study Design and Protocol Development." NeuroImage 185 (January): 891–905.
- Isensee, Fabian, Paul F. Jaeger, Simon A. A. Kohl, Jens Petersen, and Klaus H. Maier-Hein. 2021. "nnU-Net: A Self-Configuring Method for Deep Learning-Based Biomedical Image Segmentation." Nature Methods 18 (2): 203–11.
- Jenkinson, Mark, Christian F. Beckmann, Timothy E. J. Behrens, Mark W. Woolrich, and Stephen M. Smith. 2012. "FSL." NeuroImage 62 (2): 782–90.
- Paszke, Adam, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017. "Automatic Differentiation in PyTorch." https://openreview.net/pdf?id=BJJsrmfCZ.