{"repo":"AIM-Harvard/pyradiomics","free":true,"listed":false,"github":"https://github.com/AIM-Harvard/pyradiomics","clone":"git clone https://github.com/AIM-Harvard/pyradiomics.git","description":"Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics","language":"Jupyter Notebook","stars":1438,"topics":["radiomics","cancer-imaging-research","medical-imaging","computational-imaging","nci-qin","tcia-dac","python","radiomics-features","docker","nci-itcr"],"license":"BSD-3-Clause","category":"deployment-docker-iac","readme_excerpt":"pyradiomics v3.1.0 \\ Radiomics feature extraction in Python This is an open-source python package for the extraction of Radiomics features from medical imaging. With this package we aim to establish a reference standard for Radiomic Analysis, and provide a tested and maintained open-source platform for easy and reproducible Radiomic Feature extraction. By doing so, we hope to increase awareness of radiomic capabilities and expand the community. The platform supports both the feature extraction in 2D and 3D and can be used to calculate single values per feature for a region of interest (\"segment-based\") or to generate feature maps (\"voxel-based\"). Not intended for clinical use. If you publish any work which uses this package, please cite the following publication: van Griethuysen, J. J. M., Fedorov, A., Parmar, C., Hosny, A., Aucoin, N., Narayan, V., Beets-Tan, R. G. H., Fillion-Robin, J. C., Pieper, S., Aerts, H. J. W. L. (2017). Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Research, 77(21), e104–e107. https://doi.org/10.1158/0008-5472.CAN-17-0339 Join the Community! Please join the Radiomics community section of the 3D Slicer Discourse. Feature Classes Currently supports the following feature classes: - First Order Statistics - Shape-based (2D and 3D) - Gray Level Co-occurrence Matrix (GLCM) - Gray Level Run Length Matrix (GLRLM) - Gray Level Size Zone Matrix (GLSZM) - Gray Level Dependence Matrix (GLDM) - Neighboring Gray Tone Difference Matri","default_branch":null,"files":null,"tree":[],"storefront":"/r/AIM-Harvard","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AIM-Harvard/pyradiomics/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}