Difference between revisions of "Cerebellum CNN"
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− | <meta name="title" content="ACAPULCO: Cerebellum Parcellation with Convolutional Neural Networks"/> | + | <!-- <meta name="title" content="ACAPULCO: Cerebellum Parcellation with Convolutional Neural Networks"/> --> |
{{h2|Cerebellum Parcellation with Convolutional Neural Networks}} | {{h2|Cerebellum Parcellation with Convolutional Neural Networks}} | ||
{{TOCright}} | {{TOCright}} | ||
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{|align="center" style="width:75%; border:2px #e99095 solid; background:#ffffff; text-align:left;" | {|align="center" style="width:75%; border:2px #e99095 solid; background:#ffffff; text-align:left;" | ||
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− | | colspan=" | + | | colspan="3" align="center" | '''ACAPULCO''' |
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− | | {{iacl|~shuo/data/ | + | <!-- |
− | | 1. | + | | {{iacl|~shuo/data/acapulco_022.tar.gz|Docker image CPU}} |
+ | | 1.8GB | ||
|- | |- | ||
− | | {{iacl|~shuo/data/ | + | | {{iacl|~shuo/data/acapulco_022_gpu.tar.gz|Docker image GPU}} |
− | | 1. | + | | 2.5GB |
+ | |- | ||
+ | --> | ||
+ | | {{iacl|~shuo/data/acapulco_030.sif|Singularity image CPU}} | ||
+ | | Feb 27 2022 | ||
+ | | 1.8GB | ||
+ | |- | ||
+ | | {{iacl|~shuo/data/acapulco_030_gpu.sif|Singularity image GPU}} | ||
+ | | Feb 27 2022 | ||
+ | | 2.5GB | ||
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{{h3|Instructions}} | {{h3|Instructions}} | ||
− | The | + | The instructions are available [https://gitlab.com/shuohan/keras-unet-cerebellum/-/blob/master/README.md here]. |
+ | |||
+ | {{h3| Delineation protocols: region names and voxel values}} | ||
+ | |||
+ | * Adult training data: | ||
+ | "Background": 0, | ||
+ | "Corpus Medullare": 12, | ||
+ | "Left I-III": 33, | ||
+ | "Right I-III": 36, | ||
+ | "Left IV": 43, | ||
+ | "Rigt IV": 46, | ||
+ | "Left V": 53, | ||
+ | "Right V": 56, | ||
+ | "Vermis VI": 60, | ||
+ | "Left VI": 63, | ||
+ | "Right VI": 66, | ||
+ | "Vermis VII": 70, | ||
+ | "Left Crus I": 73, | ||
+ | "Left Crus II": 74, | ||
+ | "Left VIIB": 75, | ||
+ | "Right Crus I": 76, | ||
+ | "Right Crus II": 77, | ||
+ | "Right VIIB": 78, | ||
+ | "Vermis VIII": 80, | ||
+ | "Left VIIIA": 83, | ||
+ | "Left VIIIB": 84, | ||
+ | "Right VIIIA": 86, | ||
+ | "Right VIIIB": 87, | ||
+ | "Vermis IX": 90, | ||
+ | "Left IX": 93, | ||
+ | "Right IX": 96, | ||
+ | "Vermis X": 100, | ||
+ | "Left X": 103, | ||
+ | "Right X": 106 | ||
+ | |||
− | + | * Pediatric training data: | |
− | + | "Background": 0, | |
− | + | "Right Lobules I-V": 3, | |
− | + | "Right Lobule VI": 4, | |
− | + | "Right Crus I": 5, | |
− | + | "Right Crus II/VIIB": 6, | |
− | + | "Right Lobule VIII": 7, | |
− | + | "Right Lobule IX": 8, | |
− | + | "Right Lobule X": 9, | |
− | + | "Left Lobules I-V": 10, | |
− | + | "Left Lobule VI": 11, | |
− | + | "Left Crus I": 12, | |
− | + | "Left Crus II/VIIB": 13, | |
− | + | "Left Lobule VIII": 14, | |
− | + | "Left Lobule IX": 15, | |
− | + | "Left Lobule X": 16, | |
− | + | "Vermis I-V": 17, | |
− | + | "Vermis VI-VII": 18, | |
− | + | "Vermis VIII-X": 19, | |
− | + | "Corpus Medullare": 20 | |
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Latest revision as of 18:19, 2 November 2022
Cerebellum Parcellation with Convolutional Neural Networks
Automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization (ACAPULCO) is our current cerebellum parcellation method. The associated publication is:
- S. Han, A. Carass, Y. He, and J.L. Prince, "Automatic Cerebellum Anatomical Parcellation using U-Net with Locally Constrained Optimization", NeuroImage, 218:116819, 2020. (doi)
ACAPULCO | ||
Singularity image CPU | Feb 27 2022 | 1.8GB |
Singularity image GPU | Feb 27 2022 | 2.5GB |
If you use it please cite the above paper. If you have any questions, please email Shuo Han at shan50 _AT_ jhu.edu
.
Instructions
The instructions are available here.
Delineation protocols: region names and voxel values
- Adult training data:
"Background": 0, "Corpus Medullare": 12, "Left I-III": 33, "Right I-III": 36, "Left IV": 43, "Rigt IV": 46, "Left V": 53, "Right V": 56, "Vermis VI": 60, "Left VI": 63, "Right VI": 66, "Vermis VII": 70, "Left Crus I": 73, "Left Crus II": 74, "Left VIIB": 75, "Right Crus I": 76, "Right Crus II": 77, "Right VIIB": 78, "Vermis VIII": 80, "Left VIIIA": 83, "Left VIIIB": 84, "Right VIIIA": 86, "Right VIIIB": 87, "Vermis IX": 90, "Left IX": 93, "Right IX": 96, "Vermis X": 100, "Left X": 103, "Right X": 106
- Pediatric training data:
"Background": 0, "Right Lobules I-V": 3, "Right Lobule VI": 4, "Right Crus I": 5, "Right Crus II/VIIB": 6, "Right Lobule VIII": 7, "Right Lobule IX": 8, "Right Lobule X": 9, "Left Lobules I-V": 10, "Left Lobule VI": 11, "Left Crus I": 12, "Left Crus II/VIIB": 13, "Left Lobule VIII": 14, "Left Lobule IX": 15, "Left Lobule X": 16, "Vermis I-V": 17, "Vermis VI-VII": 18, "Vermis VIII-X": 19, "Corpus Medullare": 20