{"id":26509933,"url":"https://github.com/radxtools/topology-radiomics","last_synced_at":"2025-10-05T02:54:29.024Z","repository":{"id":54622261,"uuid":"282061244","full_name":"radxtools/topology-radiomics","owner":"radxtools","description":"Python implementation of topology descriptors which capture subtle sharpness and curvature differences along the surface of diseased pathologies on imaging.","archived":false,"fork":false,"pushed_at":"2021-11-18T09:47:35.000Z","size":140233,"stargazers_count":8,"open_issues_count":4,"forks_count":3,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-02-22T07:20:47.131Z","etag":null,"topics":["cancer-imaging","cancer-imaging-research","computational-imaging","docker","feature-extraction","itcr","python","radiomics","radiomics-feature-extraction","radiomics-features"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/radxtools.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-07-23T21:41:53.000Z","updated_at":"2025-02-15T04:28:46.000Z","dependencies_parsed_at":"2022-08-13T21:50:35.472Z","dependency_job_id":null,"html_url":"https://github.com/radxtools/topology-radiomics","commit_stats":null,"previous_names":["toth-technology/bric-morphology"],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radxtools%2Ftopology-radiomics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radxtools%2Ftopology-radiomics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radxtools%2Ftopology-radiomics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radxtools%2Ftopology-radiomics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/radxtools","download_url":"https://codeload.github.com/radxtools/topology-radiomics/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244722689,"owners_count":20499151,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cancer-imaging","cancer-imaging-research","computational-imaging","docker","feature-extraction","itcr","python","radiomics","radiomics-feature-extraction","radiomics-features"],"created_at":"2025-03-21T01:38:21.073Z","updated_at":"2025-10-05T02:54:23.881Z","avatar_url":"https://github.com/radxtools.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Overview\n\nTopology descriptors are designed to capture subtle sharpness and curvature differences along the surface of diseased pathologies on imaging.\n\nThese are based on the hypothesis that local structural changes through infiltration and disruption of disease in a region is likely to cause shape irregularities and in turn, resulting in changes along the surface of the lesion.\n\n# References\n\nIf you make use of this implementation, please cite the following paper:\n\nIsmail, M., Hill, V., Statsevych, V., Huang, R., Prasanna, P., Correa, R., Singh, G., Bera, K., Beig, N., Thawani, R. Madabhushi, A., Aahluwalia, M, and Tiwari, P., \"Shape features of the lesion habitat to differentiate brain tumor progression from pseudoprogression on routine multiparametric MRI: a multisite study\". American Journal of Neuroradiology, 2018, 39(12), pp.2187-2193.\n\n# Getting started with topology radiomics\n\n## Installing using pip\n\nYou can find our package on pypi\n\nRun the below command to install the package:\n\n```\npip install topology_radiomics\n```\n\n## Running with docker\n\nFirst clone this repository\n\n```\ngit clone https://github.com/radxtools/topology-radiomics.git\n```\n\nThere are multiple ways to get started.\n\n1. docker-compose\n2. docker run\n\n### docker-compose\n\nRun the following commands to start the docker container\n\n```\ncd docker\ndocker-compose up\n```\n\n### docker run\n\nWith this step, you don't need to clone the url.\nRun the following commands to start the docker container\n\n```\ndocker rm radxtools/topology-radiomics-examples\ndocker pull radxtools/topology-radiomics-examples\ndocker run -d -p 3000:3000 --name topology-radiomics-examples radxtools/topology-radiomics-examples\n```\n\n## Tutorials\n\nOnce the docker image is up and running. You can view our notebooks. You can get started with the notebook to learn how to use the package. You should start with `Tutorial - Getting started with topology_radiomics.ipynb`\n\nTutorial Notebooks:\n\n1. Tutorial - Getting started with topoplogy_radiomics.ipynb\n2. Tutorial - Using topology_radiomics to visualize features.ipynb\n3. Tutorial - Working with medpy and topology_radiomics.ipynb\n\nThe notebooks can be viewed by opening the browser and visting the url http://localhost:3000\n\n**Note:** topology_radiomics clips outliers a per lesion basis. See the tutorials for more information.\n\n\n# Contribution Guide:\n\nPlease follow google style formatting for [docstrings](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings)\n\n## Bugs and Feature Request\n\nPlease submit bugs and features to our github page.\n\n\n## Pull Requests\nCreate a issue on our board.\nCreate a pull request with your changes. Tag your changes with the issue number (commit message should have issue number).\nSomeone from the team will review your request and merge your changes for the next release.\n\n# Characteristics of Curvature\n\nThe topology of surfaces in imaging can be quantified with gaussian curvature and mean curvature. The following 4 surface measures are derived from the gaussian and mean curvatures:\n- Curvedness\n- Shape Index\n- Sharpness\n- Total Curvature\n\nThe figure below highlights characteristics of the gaussian and mean curvatures, as well as some of the surface measures.\n\n\u003ca href='https://www.researchgate.net/publication/307303825_Heritability_maps_of_human_face_morphology_through_large-scale_automated_three-dimensional_phenotyping'\u003e![Characteristics of Curvatures](images/Characteristics_of_curvature.png)\u003c/a\u003e\n\nThis figure was adapted from:\n\n\u003cdiv align='center'\u003eTsagkrasoulis, Dimosthenis \u0026 Hysi, Pirro \u0026 Spector, Tim \u0026 Montana, Giovanni. (2016). Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping. Scientific Reports. 7. 10.1038/srep45885.\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fradxtools%2Ftopology-radiomics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fradxtools%2Ftopology-radiomics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fradxtools%2Ftopology-radiomics/lists"}