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Data released on October 21, 2016

LORIS: DICOM anonymizer

Das, S; Madjar, C; Mohades, Z; Sengupta, A (2016): LORIS: DICOM anonymizer GigaScience Database. RIS BibTeX Text

The purpose of this Brainhack project was to create a simple application, with the least dependencies, for anonymization of DICOM files directly on a workstation.
Anonymization of DICOM datasets is a requirement before an imaging study can be uploaded in a web-based database system, such as LORIS. Currently, a simple and efficient interface for the anonymization of such imaging datasets, which works on all operating systems and is very light in terms of dependencies, is not available.
Here, we created a DICOM anonymizer that is a simple graphical tool that uses PyDICOM package to anonymize DICOM datasets easily on any operating system, with no dependencies except for the default Python and NumPy packages. DICOM anonymizer is available for all UNIX systems (including Mac OS) and can be easily installed on Windows computers as well (see PyDICOM installation). The GUI (using tkinter) and the processing pipeline were designed in Python. Executing the script with a python compiler will start the program. Figure 1 illustrates how to use the program to anonymize a DICOM study.
The DICOM anonymizer is a simple standalone graphical tool that facilitates anonymization of DICOM datasets on any operating system. These anonymized studies can be uploaded to a web-based database system, such as LORIS, without compromising the patient or participant’s identity.

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Related datasets:

doi:10.5524/100220 IsPartOf doi:10.5524/100215

Additional information:

Neuroscience, Imaging

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