--- license: cc-by-4.0 tags: - medical-imaging - anatomy - ultrasound - computed-tomography - image-classification task_categories: - image-classification --- # OrganScan training corpus — recipe and provenance This repository publishes the **recipe**, not the pixels. Medical imaging corpora carry licences that differ source by source, and several forbid redistribution outright. More importantly, frames rendered from DICOM can carry burned-in patient identifiers even after tag-level de-identification. Rather than ship images that are easy to misuse, this repo contains everything needed to rebuild the corpus from the pinned upstream releases. ## What is here | File | Purpose | |---|---| | `sources.json` | Every source with its pinned revision, checksum, licence, access status, and training decision | | `anatomy-tiers.json` | The three-level taxonomy, the organ -> region parent map, and which classes are actually trained | | `anatomy-mappings.json` | Explicit decision for every upstream class and DICOM tag value; no default branch | | `canonical-frame-row.schema.json` | The row schema every source is normalised to | | `preprocessor.json` | Exact pixel handling, so a rebuild is byte-comparable | | `build-manifest.json` | Counts by split, source, modality, organ — and **patients**, not just frames | ## Corpus shape | Split | Frames | Patients | |---|---:|---:| | train | 82,354 | see `build-manifest.json` | | validation | 10,280 | see `build-manifest.json` | | test | 15,395 | see `build-manifest.json` | | Modality | Frames | |---|---:| | CT | 83,318 | | MR | 1,880 | | US | 14,907 | | XR | 7,924 | ## Why patient counts are printed next to frame counts 300 consecutive frames from one cine loop carry roughly the information of one sample. MedMNIST OrganAMNIST is 58,830 images from **201** CT scans — 293 images per patient. Training on the raw count inflates every metric and teaches the model scanner identity. `sampling_policy` in `sources.json` caps frames per patient before anything is written, and the builder enforces it. ## Redistribution status by source | Source | Licence | Access | Redistributed here | |---|---|---|---| | `medmnist-plus-organamnist-224` | CC-BY-4.0 | open | recipe only | | `medmnist-plus-organcmnist-224` | CC-BY-4.0 | open | recipe only | | `medmnist-plus-organsmnist-224` | CC-BY-4.0 | open | recipe only | | `medmnist-plus-breastmnist-224` | CC-BY-4.0 | open | recipe only | | `medmnist-plus-chestmnist-224` | CC-BY-4.0 | open | recipe only | | `msu-abdominal-ultrasound` | CC-BY-4.0 | open_manual_browser_download | recipe only | | `fetal-planes-db` | CC-BY-4.0 | open | recipe only | | `totalsegmentator-ct-sample` | CC-BY-4.0 | open | recipe only | | `totalsegmentator-ct-v300` | CC-BY-4.0 | open | recipe only | | `amos22` | CC-BY-4.0 | open | recipe only | | `medical-segmentation-decathlon` | CC-BY-SA-4.0 | open_but_unresolved_host | recipe only | | `rocov2` | CC-BY-NC-4.0 | open | **no** — licence forbids | | `radimagenet` | undefined | registration_and_agreement_required | **no** — licence forbids | | `camus` | undefined | registration_required | **no** — licence forbids | | `echonet-dynamic` | Stanford EchoNet-Dynamic Dataset Research Use Agreement | signed_research_use_agreement | **no** — licence forbids | | `echonet-lvh` | Stanford EchoNet-LVH Dataset Research Use Agreement | signed_research_use_agreement | **no** — licence forbids | | `busi-original` | undefined | mirror_only | **no** — licence forbids | | `tn3k` | undefined | third_party_drive | **no** — licence forbids | | `ddti` | undefined | source_site_unavailable | **no** — licence forbids | | `mmotu` | undefined | third_party_drive | **no** — licence forbids | | `pocus-covid19-ultrasound` | mixed per-file (CC-BY-4.0, CC-BY-NC-4.0, all-rights-reserved) | open | **no** — licence forbids | | `biomedclip` | MIT tag, but the model card restricts use | open | **no** — licence forbids | | `usfm` | CC-BY-NC-4.0 | third_party_drive | **no** — licence forbids | ## Rebuild it ```bash git clone https://github.com/palarnab/organscan && cd organscan python downloaded-training-data/download.py # pinned revisions, checksum-verified python scripts/build_frame_dataset.py python scripts/validate_frame_dataset.py # leakage, mask coherence, coverage ``` The build fails rather than silently dropping data when an unmapped upstream class appears, and validation fails on patient leakage across splits, identical frames in two splits, or a weak label found in an evaluation split. ## Attribution Every source below requires credit, and every one of them was modified — sliced from volumes or cine loops, windowed, resized to 224×224, capped per patient, and relabelled into the OrganScan taxonomy. Full per-source detail, including the exact modifications, is in `sources.json` under each entry's `attribution` block. | Source | Creators | Licence | Frames used | |---|---|---|---:| | [TotalSegmentator CT dataset v3.0.0](https://zenodo.org/records/22688904) | Jakob Wasserthal et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 61,902 | | [AMOS22: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation](https://zenodo.org/records/7262581) | Yuanfeng Ji et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 11,480 | | [FETAL_PLANES_DB: Common maternal-fetal ultrasound images](https://zenodo.org/records/3904280) | Xavier P. Burgos-Artizzu et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 10,748 | | [MedMNIST v2 (ChestMNIST, 224px)](https://zenodo.org/records/10519652) | Jiancheng Yang et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 7,924 | | [MedMNIST v2 (OrganSMNIST, 224px)](https://zenodo.org/records/10519652) | Jiancheng Yang et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 4,000 | | [MedMNIST v2 (OrganAMNIST, 224px)](https://zenodo.org/records/10519652) | Jiancheng Yang et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 3,914 | | [MedMNIST v2 (OrganCMNIST, 224px)](https://zenodo.org/records/10519652) | Jiancheng Yang et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 3,902 | | [Abdominal Ultrasound Image Dataset for Organ Classification and Disease Detection](https://scholarsjunction.msstate.edu/research-data/5/) | Sifat Zina Karim | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 3,380 | | [MedMNIST v2 (BreastMNIST, 224px)](https://zenodo.org/records/10519652) | Jiancheng Yang et al. | [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) | 779 | ``` OrganScan is trained on the following datasets, all of which were modified (sliced to 2D, windowed, resized to 224px, and relabelled): - TotalSegmentator CT dataset v3.0.0 Jakob Wasserthal, Hanns-Christian Breit, Manfred T. Meyer, Maurice Pradella, Daniel Hinck, Alexander W. Sauter, Tobias Heye, Daniel T. Boll, Joshy Cyriac, Shan Yang, Michael Bach, Martin Segeroth - CC-BY-4.0 https://zenodo.org/records/22688904 - AMOS22: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation Yuanfeng Ji, Haotian Bai, Chongjian Ge, Jie Yang, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, Ping Luo - CC-BY-4.0 https://zenodo.org/records/7262581 - FETAL_PLANES_DB: Common maternal-fetal ultrasound images Xavier P. Burgos-Artizzu, David Coronado-Gutierrez, Brenda Valenzuela-Alcaraz, Elisenda Bonet-Carne, Elisenda Eixarch, Fatima Crispi, Eduard Gratacós - CC-BY-4.0 https://zenodo.org/records/3904280 - MedMNIST v2 (ChestMNIST, 224px) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bilian Ke, Hanspeter Pfister, Bingbing Ni - CC-BY-4.0 https://zenodo.org/records/10519652 - MedMNIST v2 (OrganSMNIST, 224px) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bilian Ke, Hanspeter Pfister, Bingbing Ni - CC-BY-4.0 https://zenodo.org/records/10519652 - MedMNIST v2 (OrganAMNIST, 224px) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bilian Ke, Hanspeter Pfister, Bingbing Ni - CC-BY-4.0 https://zenodo.org/records/10519652 - MedMNIST v2 (OrganCMNIST, 224px) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bilian Ke, Hanspeter Pfister, Bingbing Ni - CC-BY-4.0 https://zenodo.org/records/10519652 - Abdominal Ultrasound Image Dataset for Organ Classification and Disease Detection Sifat Zina Karim - CC-BY-4.0 https://scholarsjunction.msstate.edu/research-data/5/ - MedMNIST v2 (BreastMNIST, 224px) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bilian Ke, Hanspeter Pfister, Bingbing Ni - CC-BY-4.0 https://zenodo.org/records/10519652 ``` ## Author Arnab Pal — [LinkedIn](https://www.linkedin.com/in/pal-arnab) · [GitHub](https://github.com/palarnab)