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Our aim was to investigate whether sex can be determined from a combination of geometric features obtained from the 10th thoracic vertebra, 6th rib, and 7th rib. Six hundred chest radiographs (300 males and 300 females) were randomly selected to include patients of six age groups (20s, 30s, 40s, 50s, 60s, and 70s). Each group included 100 images (50 males and 50 females). A total of 14 features, including 7 lengths, 5 indices for the vertebra, and 2 types of widths for ribs, were utilized and analyzed for sex determination. Dominant features contributing to sex determination were selected by stepwise discriminant analysis after checking the variance inflation factors for multicollinearity. The accuracy of sex determination using a combination of the vertebra and ribs was evaluated from the selected features by the stepwise discriminant analysis. The accuracies in each age group were also evaluated in this study. The accuracy of sex determination based on a combination of features of the vertebra and ribs was 88.8% (533/600). This performance was superior to that of the vertebra or ribs only. Moreover, sex determination of subjects in their 20s demonstrated the highest accuracy (96.0%, 96/100). The features selected in the stepwise discriminant analysis included some features in both the vertebra and ribs. These results indicate the usefulness of combined information obtained from the vertebra and ribs for sex determination. We conclude that a combination of geometric characteristics obtained from the vertebra and ribs could be useful for determining sex.

This study revealed the usefulness of volumetric analysis of mastoid air cells (MACs) extracted from postmortem computed tomography (PMCT) images in characterizing individuals. To characterize deceased persons, the MACs volumes of 61 Japanese PMCT images were measured after thresholding in Hounsfield units and based on the number of voxels on the right and left sides and the voxel size for each person. The volume differences between the right and left MACs and sex were examined. Although there were no obvious volume differences between males and females, the order of sizes on the two sides varied for each person. Moreover, deceased persons could be roughly classified using the total volume of MACs. Deceased persons with similar total volumes could be distinguished further by comparing the ratio of volumes in bilateral MACs. Although the identification process is dependent on samples and different sizes of bilateral MACs, our pilot study indicated that 81.9% (50/61) of deceased persons could be distinguished. In conclusion, volumetric analysis of MACs measured using PMCT imaging has the potential to identify individuals and reduce the number of candidates.

The aim of this study is to examine the usefulness of bone structure extracted data from chest computed tomography (CT) images for personal identification. Eighteen autopsied cases (12 male and 6 female) that had ante- and post-mortem (AM and PM) CT images were used in this study. The two-dimensional (2D) and threedimensional (3D) bone images were extracted from the chest CT images via thresholding technique. The similarity between two thoracic bone images (consisting of vertebrae, ribs, and sternum) acquired from AMCT and PMCT images was calculated in terms of the normalized cross-correlation value (NCCV) in both 2D and 3D matchings. An AM case with the highest NCCV corresponding to a given PM case among all of the AM cases studied was regarded as same person. The accuracy of identification of the same person using our method was 100% (18/18) in both 2D and 3D matchings. The NCCVs for the same person tended to be significantly higher than the average of NCCVs for different people in both 2D and 3D matchings. The computation times of image similarity between the two images were less than one second and approximately 10 min in 2D and 3D matching, respectively. Therefore, 2D matching especially for thoracic bones seems more advantageous than 3D matching with regard to computation time. We conclude that our proposed personal identification method using bone structure would be useful in forensic cases.

This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s12194-022-00682-2., Immediate verification of whether a patient being examined is correct is desirable, even if the scan ranges change during different examinations for the same patient. This study proposes an advanced biological fingerprint technique for the rapid and reliable verification of various scan ranges in computed tomography (CT) scans of the torso of the same patient. The method comprises the following steps: geometric correction of different scans, local feature extraction, mismatch elimination, and similarity evaluation. The geometric magnification correction was aligned at the scanner table height in the first two steps, and the local maxima were calculated as the local features. In the third step, local features from the follow-up scout image are matched to those in the corresponding baseline scout image via template matching and outlier elimination via a robust estimator. We evaluated the correspondence rate based on the inlier ratio between corresponding scout images. The ratio of inliers between the baseline and follow-up scout images was assessed as the similarity score. The clinical dataset, including chest, abdomen–pelvis, and chest–abdomen–pelvis scans, included 600 patients (372 men, 68 ± 12years) who underwent two routine torso CT examinations. The highest area under the receiver operating characteristic curve (AUC) was 0.996, which was sufficient for patient verification. Moreover, the verification results were comparable to the conventional method, which uses scout images in the same scan range. Patient identity verification was achieved before the main scan, even in follow-up torso CT, under different scan ranges.