Title:Reproducibility of Facial Information in Three-Dimensional Reconstructed
Head Images: An Exploratory Study
Volume: 19
Author(s): Tatsuya Uchida, Taichi Kin*, Katsuya Sato, Tsukasa Koike, Satoshi Kiyofuji, Yasuhiro Takeda, Ryoko Niwa, Toki Saito, Ikumi Takashima, Takuya Kawahara, Satoru Miyawaki, Hiroshi Oyama and Nobuhito Saito
Affiliation:
- Department of Neurosurgery, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
Keywords:
Biomedical imaging, computed tomography, face recognition, personally identifiable information, threedimensional reconstruction, face detection.
Abstract:
Background: Facial information acquired via three-dimensional reconstruction of head
computed tomography (CT) data may be considered personal information, which can be problematic
for neuroimaging studies. However, no study has verified the relationship between slice thickness and
face reproducibility. This study determined the relationship and match rate between image slice thickness
and face detection accuracy of face-recognition software in facial reconstructed models.
Methods: Head CT data of 60 cases comprising entire faces obtained under conditions of non-contrast
and 1-mm slice thickness were resampled to obtain 2-10-mm slice-thickness data. Facial models, reconstructed
by image thresholding, were acquired from the data. We performed face detection tests per
slice thickness on the models and calculated the face detection rate. The reconstructed facial models
created from 1-mm slice-thickness data and other slice thicknesses were used as training and test data,
respectively. Match confidence scores were obtained via three programs, match rates were calculated
per slice thickness, and generalized estimating equations were used to evaluate the match rate trend.
Results: In general, the face detection rates for the 1-10-mm slice thicknesses were 100, 100, 98.3,
98.3, 95.0, 91.7, 86.7, 78.3, 68.3, and 61.7 %, respectively. The match rates for the 2-10-mm slice
thicknesses were 100, 98.3, 98.3, 95.0, 85.0, 71.7, 53.3, 28.3, and 16.7 %, respectively.
Conclusion: The reconstructed models tended to have higher match rates as the slice thickness decreased.
Thus, thin-slice head CT imaging data may increase the possibility of the information becoming
personally identifiable health information.
