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Build and certify a single free tool that strips names and identifying marks from cancer scans and pathology slides, so every hospital stops writing its own.
Every institution that shares imaging builds or buys its own DICOM de-identification, with inconsistent handling of burned-in text, private tags and slide label images. The Cancer Imaging Archive has curation experience and there are open tools (for example the RSNA anonymizer and CTP), but no certified reference implementation for whole-slide images or radiotherapy objects. The proposal funds a maintained open pipeline with a public test corpus of adversarial cases and an independent certification.
Shares AI that is built but not validated or deployed, Digital pathology & AI, Data silos.
Shares CT (computed tomography), Data silos, MRI.
Shares AI that is built but not validated or deployed, Digital pathology & AI, Data silos.
Shares AI that is built but not validated or deployed, CT (computed tomography), MRI.
Shares AI that is built but not validated or deployed, Data silos.
Shares AI that is built but not validated or deployed, Digital pathology & AI.
Shares AI that is built but not validated or deployed, CT (computed tomography).
Shares CT (computed tomography), MRI.