{"access":"open","annotations":"Varies by collection: from unlabelled scans to expert segmentations (DICOM-SEG/RTSTRUCT), radiomics features and outcome data; each collection has its own data card.","article":null,"cancer_slugs":["pan-cancer"],"details":"","doi":null,"formats":["DICOM","NIfTI","CSV"],"hf":null,"huggingface":null,"kind":"registry","license":"mostly CC BY 3.0/4.0 per collection; some restricted collections","modalities":["radiology-ct","radiology-mri","pet","mammography","histopathology","radiology-xray"],"models":[{"name":"MedSAM","note":"many TCIA collections are in the 1.57M-pair training set","role":"training","slug":"medsam"}],"name":"TCIA \u2014 The Cancer Imaging Archive","page":"/ai-oncology/datasets/tcia","provider":"NCI Cancer Imaging Program; hosted by the University of Arkansas for Medical Sciences","size":{"items":200,"notes_en":"hundreds of collections, tens of thousands of patients; DICOM with linked clinical and sometimes genomic data","notes_pl":"setki kolekcji, dziesi\u0105tki tysi\u0119cy pacjent\u00f3w; DICOM z powi\u0105zanymi danymi klinicznymi, czasem genomowymi","unit":"collections"},"slug":"tcia","sources":[{"label":"The Cancer Imaging Archive","url":"https://www.cancerimagingarchive.net/"}],"summary":"The main public archive of de-identified cancer imaging, organised into collections by disease and modality; the source of most public radiology training data in oncology.","tasks":["segmentation","detection","classification","prognosis"],"url":"https://www.cancerimagingarchive.net/","verified_at":"2026-09-05T22:25:58.836069"}