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Reproducibility of Facial Information in Three-Dimensional Reconstructed Head Images: An Exploratory Study.

Tatsuya Uchida¹, Taichi Kin¹, Katsuya Sato¹

¹Department of Neurosurgery, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.

Current Medical Imaging

|January 25, 2023

Summary

Thinner slice thickness in head CT scans increases the accuracy of 3D facial reconstruction, potentially identifying individuals. This highlights risks for patient privacy in neuroimaging studies using computed tomography (CT) data.

Keywords:

Biomedical imaging computed tomography face detection face recognition personally identifiable information threedimensional reconstruction

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Area of Science:

Medical Imaging
Radiology
Computer Vision

Background:

Facial data from 3D head CT reconstructions may be considered personal information.
This poses challenges for neuroimaging studies concerning patient privacy.
The relationship between CT slice thickness and facial reconstruction accuracy is not well-established.

Purpose of the Study:

To determine the relationship between computed tomography (CT) slice thickness and face detection accuracy.
To assess the match rate of facial recognition software with 3D reconstructed models from varying CT slice thicknesses.

Main Methods:

Head CT data (1-mm slice thickness) from 60 cases were resampled to create 2-10-mm slice thickness datasets.
3D facial models were reconstructed using image thresholding.
Face detection tests and match rate calculations were performed using three facial recognition programs.

Main Results:

Face detection rates generally decreased as slice thickness increased, with 100% detection for 1-2 mm slices.
Match rates significantly decreased with increasing slice thickness, dropping to 16.7% at 10 mm.
Facial models reconstructed from thinner slices showed higher match rates.

Conclusions:

Decreasing slice thickness in head CT scans enhances the reproducibility of 3D facial reconstructions.
Thin-slice CT data increases the likelihood of facial information being identifiable.
This has implications for the management of personally identifiable health information in medical imaging.