Collection Pseudo-PHI-DICOM-Data
Details
Subject Count: 42
Primary Site: Various
Image Modalities: CR, CT, DX, MG, MR, PT
Cancer Type(s): Various
Species: Human
DOIs
Pseudo-PHI-DICOM-Data original data:
Description
The process of image de-identification is time consuming, requires significant human resources, and is prone to human error. Automated image de-identification algorithms have been developed but the research community requires some method of evaluation before such tools can be widely accepted. This evaluation requires a robust dataset that can be used as part of an evaluation process for de-identification algorithms. We developed a DICOM dataset that can be used to evaluate the performance of de-identification algorithms.
Please see the Medical Imaging De-Identification Initiative (MIDI) wiki page to learn more about the images and to obtain any supporting metadata for this collection.