magiccluster 0.0.3

Multi-scale semi-supervised clustering

MAGIC

Multi-scAle heteroGeneity analysIs and Clustering

Documentation

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.

:warning: 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