MAGIC
Multi-scAle heteroGeneity analysIs and Clustering
MLNI
MAGIC, Multi-scAle heteroGeneity analysIs and Clustering, is a multi-scale semi-supervised clustering method that aims to derive robust clustering solutions across different scales for brain diseases.
⚠️ The documentation of this software is currently under development
Citing this work
If you use this software for clustering:
Wen J., Varol E., Chand G., Sotiras A., Davatzikos C. (2020) MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12267. Springer, Cham. https://doi.org/10.1007/978-3-030-59728-3_66
Wen J., Varol E., Chand G., Sotiras A., Davatzikos C. (2022) Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes. Medical Image Analysis, 2022. https://doi.org/10.1016/j.media.2021.102304 - Link
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Metadata
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Release files for magiccluster 0.0.3
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| File | Size | Uploaded | Provenance | Actions |
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| magiccluster-0.0.3.tar.gz | 16.5 kB | Without provenance | Details for magiccluster-0.0.3.tar.gz |
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| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| magiccluster-0.0.3-py3-none-any.whl | Python 3 | none | any | Details for magiccluster-0.0.3-py3-none-any.whl |
Total release size: 36.8 kB
Release files / magiccluster-0.0.3.tar.gz
| Download URL | magiccluster-0.0.3.tar.gz |
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Release files / magiccluster-0.0.3-py3-none-any.whl
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| Tags | Python 3 |
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