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22 November 2023 Anonymization and validation of three-dimensional volumetric renderings of computed tomography data using commercially available T1-weighted magnetic resonance imaging-based algorithms
Rahil Patel, Destie Provenzano, Murray H. Loew
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Journal of Medical Imaging, Vol. 10, Issue 6, 066501 (November 2023). https://doi.org/10.1117/1.JMI.10.6.066501
Abstract

Purpose

Previous studies have demonstrated that three-dimensional (3D) volumetric renderings of magnetic resonance imaging (MRI) brain data can be used to identify patients using facial recognition. We have shown that facial features can be identified on simulation-computed tomography (CT) images for radiation oncology and mapped to face images from a database. We aim to determine whether CT images can be anonymized using anonymization software that was designed for T1-weighted MRI data.

Approach

Our study examines (1) the ability of off-the-shelf anonymization algorithms to anonymize CT data and (2) the ability of facial recognition algorithms to identify whether faces could be detected from a database of facial images. Our study generated 3D renderings from 57 head CT scans from The Cancer Imaging Archive database. Data were anonymized using AFNI (deface, reface, and 3Dskullstrip) and FSL’s BET. Anonymized data were compared to the original renderings and passed through facial recognition algorithms (VGG-Face, FaceNet, DLib, and SFace) using a facial database (labeled faces in the wild) to determine what matches could be found.

Results

Our study found that all modules were able to process CT data and that AFNI’s 3Dskullstrip and FSL’s BET data consistently showed lower reidentification rates compared to the original.

Conclusions

The results from this study highlight the potential usage of anonymization algorithms as a clinical standard for deidentifying brain CT data. Our study demonstrates the importance of continued vigilance for patient privacy in publicly shared datasets and the importance of continued evaluation of anonymization methods for CT data.
© 2023 Society of Photo-Optical Instrumentation Engineers (SPIE)
Citation Download Citation
Rahil Patel, Destie Provenzano, and Murray H. Loew "Anonymization and validation of three-dimensional volumetric renderings of computed tomography data using commercially available T1-weighted magnetic resonance imaging-based algorithms," Journal of Medical Imaging 10(6), 066501 (22 November 2023). https://doi.org/10.1117/1.JMI.10.6.066501
Received: 14 March 2023; Accepted: 7 November 2023; Published: 22 November 2023
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KEYWORDS
Computed tomography
Detection and tracking algorithms
Facial recognition systems
Magnetic resonance imaging
3D image processing
Head
Brain
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