{"id":13709182,"url":"https://github.com/EIDOSLAB/UNITOPATHO","last_synced_at":"2025-05-06T15:32:21.505Z","repository":{"id":82117004,"uuid":"337362995","full_name":"EIDOSLAB/UNITOPATHO","owner":"EIDOSLAB","description":"Dataset of 9536 H\u0026E-stained patches for colorectal polyps classification and adenomas grading | ICIP21 https://doi.org/10.1109/ICIP42928.2021.9506198","archived":false,"fork":false,"pushed_at":"2023-05-18T14:53:57.000Z","size":3338,"stargazers_count":31,"open_issues_count":1,"forks_count":5,"subscribers_count":3,"default_branch":"main","last_synced_at":"2024-12-08T05:03:09.097Z","etag":null,"topics":["cancer","data","health","histopathological-image","histopathology","histopathology-images","medical-image-processing","medical-images","neural-networks"],"latest_commit_sha":null,"homepage":"https://ieee-dataport.org/open-access/unitopatho","language":"Jupyter Notebook","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/EIDOSLAB.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-02-09T10:09:02.000Z","updated_at":"2024-12-01T06:45:41.000Z","dependencies_parsed_at":null,"dependency_job_id":"9453c96a-6836-4ee0-ab96-07e4eddecc46","html_url":"https://github.com/EIDOSLAB/UNITOPATHO","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EIDOSLAB%2FUNITOPATHO","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EIDOSLAB%2FUNITOPATHO/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EIDOSLAB%2FUNITOPATHO/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EIDOSLAB%2FUNITOPATHO/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EIDOSLAB","download_url":"https://codeload.github.com/EIDOSLAB/UNITOPATHO/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252713016,"owners_count":21792410,"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","data","health","histopathological-image","histopathology","histopathology-images","medical-image-processing","medical-images","neural-networks"],"created_at":"2024-08-02T23:00:36.560Z","updated_at":"2025-05-06T15:32:21.499Z","avatar_url":"https://github.com/EIDOSLAB.png","language":"Jupyter Notebook","readme":"# UNITOPATHO \n## A Labeled Histopathological Dataset for Colorectal Polyps Classification and Adenoma Dysplasia Grading\n\nCarlo Alberto Barbano\u003csup\u003e1\u003c/sup\u003e, Daniele Perlo\u003csup\u003e1\u003c/sup\u003e, Enzo Tartaglione\u003csup\u003e1\u003c/sup\u003e, Attilio Fiandrotti\u003csup\u003e1\u003c/sup\u003e, Luca Bertero\u003csup\u003e2\u003c/sup\u003e, Paola Cassoni\u003csup\u003e2\u003c/sup\u003e, Marco Grangetto\u003csup\u003e1\u003c/sup\u003e \n| [[pdf](https://ieeexplore.ieee.org/document/9506198)]\n\n\n1\u003csub\u003eUniversity of Turin, Computer Science dept.\u003c/sub\u003e\u003cbr\u003e\n2\u003csub\u003eUniversity of Turin, Medical Sciences dept.\u003c/sub\u003e\n\u003cbr/\u003e\n\n![UniToPatho](assets/unitopatho.png)\n\n*UniToPatho* is an annotated dataset of **9536** hematoxylin and eosin stained patches extracted from 292 whole-slide images, meant for training deep neural networks for colorectal polyps classification and adenomas grading. The slides are acquired through a Hamamatsu Nanozoomer S210 scanner at 20× magnification (0.4415 μm/px). Each slide belongs to a different patient and is annotated by expert pathologists, according to six classes as follows:\n\n\n- **NORM** - Normal tissue;\n- **HP** - Hyperplastic Polyp;\n- **TA.HG** - Tubular Adenoma, High-Grade dysplasia;\n- **TA.LG** - Tubular Adenoma, Low-Grade dysplasia;\n- **TVA.HG** - Tubulo-Villous Adenoma, High-Grade dysplasia;\n- **TVA.LG** - Tubulo-Villous Adenoma, Low-Grade dysplasia.\n\n\n## Downloading the dataset\n\nYou can download UniToPatho from [IEEE-DataPort](https://ieee-dataport.org/open-access/unitopatho)\n\n## Dataloader and example usage\n\nWe provide a [PyTorch compatible dataset class](/unitopatho.py) and [ECVL compatible dataloader](/unitopatho_ecvl.py).\nFor example usage see [Example.ipynb](/Example.ipynb)\n\n## Citation\n\nIf you use this dataset, please make sure to cite the [related work](https://arxiv.org/abs/2101.09991):\n\n[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/unitopatho-a-labeled-histopathological/colorectal-polyps-characterization-on)](https://paperswithcode.com/sota/colorectal-polyps-characterization-on?p=unitopatho-a-labeled-histopathological)\n\n```\n@INPROCEEDINGS{barbano2021unitopatho,\n  author={Barbano, Carlo Alberto and Perlo, Daniele and Tartaglione, Enzo and Fiandrotti, Attilio and Bertero, Luca and Cassoni, Paola and Grangetto, Marco},\n  booktitle={2021 IEEE International Conference on Image Processing (ICIP)}, \n  title={Unitopatho, A Labeled Histopathological Dataset for Colorectal Polyps Classification and Adenoma Dysplasia Grading}, \n  year={2021},\n  volume={},\n  number={},\n  pages={76-80},\n  doi={10.1109/ICIP42928.2021.9506198}\n}\n```\n","funding_links":[],"categories":["Data"],"sub_categories":["Datasets"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FEIDOSLAB%2FUNITOPATHO","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FEIDOSLAB%2FUNITOPATHO","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FEIDOSLAB%2FUNITOPATHO/lists"}