DICAT | Tool to anonymize DICOM data headers | Messaging library

DICAT is a Python library typically used in Messaging applications. DICAT has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However DICAT build file is not available. You can download it from GitHub.

DICAT is a simple graphical tool that facilitates DICOM (Digital Imaging and Communications in Medicine) de-identification directly on a local workstation. It was designed to work on all major operating systems (Windows, Linux and OSX) and is very light in terms of dependencies (Python). Binaries (with no dependencies) have been compiled for all operating systems and made available with each release of DICAT. With the increasing use of web-based database systems, such as LORIS (Das et al., 2011, Das et al., 2016), for large scale imaging studies, de-identification of DICOM datasets becomes a requirement before they can be uploaded in such databases. Before DICOM datasets can be uploaded into a web-based database, identifying information stored in the DICOM header (such as patient name, date of birth) should be removed. DICAT produces two archival outputs: a back-up of the original DICOM files, and a de-identified DICOM dataset that can then be uploaded or transferred to other systems. DICAT also features an ID key log that can be used to keep a record of the original candidate name (participant/patient) linked to their anonymized study identifier, for reference by study coordinators. DICAT was first developed during the 2014 and 2015 brainhacks held at the Organization of Human Brain Mapping (OHBM) conferences.