{"id":23555567,"url":"https://github.com/kostrykin/rfove","last_synced_at":"2025-11-01T16:30:19.444Z","repository":{"id":206877818,"uuid":"717670402","full_name":"kostrykin/rfove","owner":"kostrykin","description":"Region-based Fitting of Overlapping Ellipses (original implementation by C. Panagiotakis and A.A. 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Both RFOVE and DEFA solve the multi-ellipse fitting problem by performing model selection that is guided by the minimization of the Akaike Information Criterion on a suitably defined shape complexity measure. However, in contrast to DEFA, RFOVE minimizes an objective function that allows for ellipses with higher degree of overlap and, thus, achieves better ellipse-based shape approximation.\n\nThe Docker image uses the [original MATLAB implementation](https://de.mathworks.com/matlabcentral/fileexchange/74200-cell-segmentation-rfove-method) and makes it accessible without requiring any dependencies or license keys. [LICENSE](https://github.com/kostrykin/rfove/blob/master/rfove/LICENSE) applies to the original implementation.\n\n## [Docker instructions]()\n\nEither build or pull the image:\n\n- **Build image:** (only recommended for development)\n  ```bash\n  docker build --no-cache --tag kostrykin/rfove .\n  ```\n- **Pull image:** (recommended for production use)\n  ```bash\n  docker build --no-cache --tag kostrykin/rfove .\n  ```\n\nRun RFOVE:\n```bash\ndocker run --rm -ti \\\n  -v /tmp/io:/io kostrykin/rfove \\\n  /rfove 250 0.1 0.2 201 /io/input.png /io/seg.tiff\n```\nIn this example, the image `/tmp/io/input.png` is segmented and the results are written to `/tmp/io/seg.tiff`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkostrykin%2Frfove","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkostrykin%2Frfove","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkostrykin%2Frfove/lists"}