{"id":49628643,"url":"https://github.com/scientificcomputing/mri2mesh","last_synced_at":"2026-05-05T09:06:41.417Z","repository":{"id":268686108,"uuid":"902759428","full_name":"scientificcomputing/mri2mesh","owner":"scientificcomputing","description":"Brain meshing pipeline from MRI using pyvista, scikit-image and ftetwild","archived":false,"fork":false,"pushed_at":"2026-02-26T07:59:03.000Z","size":741,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"main","last_synced_at":"2026-02-26T12:57:05.092Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://scientificcomputing.github.io/mri2mesh/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/scientificcomputing.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2024-12-13T08:00:42.000Z","updated_at":"2026-02-26T07:59:04.000Z","dependencies_parsed_at":null,"dependency_job_id":"eb00596b-7d27-497e-9f28-d46f2c680b3f","html_url":"https://github.com/scientificcomputing/mri2mesh","commit_stats":null,"previous_names":["scientificcomputing/mri2mesh"],"tags_count":4,"template":false,"template_full_name":null,"purl":"pkg:github/scientificcomputing/mri2mesh","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientificcomputing%2Fmri2mesh","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientificcomputing%2Fmri2mesh/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientificcomputing%2Fmri2mesh/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientificcomputing%2Fmri2mesh/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/scientificcomputing","download_url":"https://codeload.github.com/scientificcomputing/mri2mesh/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientificcomputing%2Fmri2mesh/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32642366,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-04T10:08:07.713Z","status":"online","status_checked_at":"2026-05-05T02:00:06.033Z","response_time":54,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":[],"created_at":"2026-05-05T09:06:38.658Z","updated_at":"2026-05-05T09:06:41.408Z","avatar_url":"https://github.com/scientificcomputing.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# mri2mesh\n\nThis repository contains a pipeline to generate surfaces from voxelized data using `scikit-image` and `pyvista`. It also contains tools for visualization using `pyvista`.\n\n## Installation\n\nTo install the required packages, run:\n\n```bash\npython3 -m pip install git+https://github.com/scientificcomputing/mri2mesh.git\n```\n\n## Usage\nThe basic using is through the command line using the command `mri2mesh`. To see all the options, run:\n\n```bash\nmri2mesh --help\n```\n\n### Visualization\nVisualization is achieved through the subcommand `viz`. To see all options you can do\n\n```bash\nmri2mesh viz --help\n```\n\nFor example to visualize a nifty file called `T1_synthseg.nii.gz`, run:\n\n```bash\nmri2mesh viz volume-clip -i T1_synthseg.nii.gz\n```\nwhich will open up the volume with a clipping plane. To see all the options, run:\n\n```bash\nmri2mesh viz volume-clip --help\n```\n\n### Surface generation\nTo generate the parenchyma surface from a nifty file, run:\n\n```bash\nmri2mesh surface parenchyma -i T1_synthseg.nii.gz\n```\n\n## Authors\nThe pipeline is developed by Marius Causemann and Henrik Finsberg.\n\n\n## License\nMIT\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fscientificcomputing%2Fmri2mesh","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fscientificcomputing%2Fmri2mesh","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fscientificcomputing%2Fmri2mesh/lists"}