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common (58.67% males and 61.48% females for the left ear; 60.00% males and 72.59% females for the right ear). Wide covering scapha helix was the most rare for the male left ear and flat helix was the most rare for the female right ear. Square and free earlobes were the most common (49.33% males and 62.96% females for the left ear; 40.00% males and 54.81% females for the right ear), whereas triangular earlobes were rarely seen. Single knob tragus (40.00% males and 37.78% females for the left ear; 37.33% males and 33.33% females for the right ear) and projection type of Darwin's tubercle (50.67% males and 40.00% females for the left ear; 48.00% males and 39.26% females for the right ear) were found to be common. Conclusion The characteristics of the bilateral external ears of male and female Uygur adults have differences, which can be used for forensic identification.
Objective To estimate sex based on patella measurements of Sichuan Han population by computed tomography three-dimensional volume reconstruction technique, and to explore the application value of patella in sex estimation. Methods CT three-dimensional volume reconstruction images of patella of 250 individuals were collected, the four measurement indicators including patellar length, patellar width, patellar thickness, and patellar volume were measured. The
-test was used to determine measurement indicators with sex differences. Fisher discriminant analysis was used to establish the sex discriminant function and the prediction accuracy was calculated by leave-one-out cross validation. Results The sex differences of the four measurement indicators had a statistical significance (
<0.05). The accuracy rate of the univariate discriminant function established by the patellar length was the highest (82.0%). The accuracy rates of the all indicators discriminant function and the stepwise discriminant functions validation. Results The sex differences of the four measurement indicators had a statistical significance (P less then 0.05). The accuracy rate of the univariate discriminant function established by the patellar length was the highest (82.0%). The accuracy rates of the all indicators discriminant function and the stepwise discriminant function were 80.4% and 81.6%, respectively. Conclusion It is feasible and accurate to estimate sex of Sichuan Han population by patella measurements with CT three-dimensional volume reconstruction technique. The method may be used as an alternative for sex estimation of Sichuan Han population when other bones with higher accuracy are not available.
Objective To develop mathematical models for skeletal age determination with multiple statistic method based on the correlation between age and the growth of the epiphysis of extremitas sternalis of clavicle in Shanxi adolescents. Methods The 562 Shanxi sternoclavicular joint samples (454 cases of modelling, 108 cases of external verification) were scanned by the thin-section computed tomography. After volume rendering was obtained, indicators such as area of epiphysis, area of metaphysis, longest diameter of epiphysis and longest diameter of metaphysis of both extremitas sternalis of clavicle were collected. Indicators such as the ratio of area of epiphysis to area of metaphysis, and the ratio of longest diameter of epiphysis to longest diameter of metaphysis of both sides were calculated. selleck kinase inhibitor Then multiple linear regression and random forest discriminant models were used to build mathematical models for age determination of adolescents. Results The obtained indicators exhibited a strong correlation with age ( to area of metaphysis had an internal validation accuracy rate (±1.0 year) of over 92% and 108 cases had an external validation accuracy rate of over 70% (±1.0 year). The out of bag error rates of random forest discriminant models were less than 2% for people over 18.0 years old (≥18.0 years old) and under 18.0 years old. The external validation accuracy rates of the 108 cases were over 80%. Conclusion The regression and discriminant models established in this study have certain reliability and accuracy and can be used in age determination of Shanxi adolescents.
Objective To compare the performance of three deep-learning models (VGG19, Inception-V3 and Inception-ResNet-V2) in automatic bone age assessment based on pelvic X-ray radiographs. Methods A total of 962 pelvic X ray radiographs taken from adolescents (481 males, 481 females) aged from 11.0 to 21.0 years in five provinces and cities of China were collected, preprocessed and used as objects of study. Eighty percent of these X ray radiographs were divided into training set and validation set with random sampling method and used for model fitting and hyper-parameters adjustment. Twenty percent were used as test sets, to evaluate the ability of model generalization. The performances of the three models were assessed by comparing the root mean square error (RMSE), mean absolute error (MAE) and Bland-Altman plots between the model estimates and the chronological ages. Results The mean RMSE and MAE between bone age estimates of the VGG19 model and the chronological ages were 1.29 and 1.02 years, respectively. The ception-ResNet-V2 model and the chronological ages was the lowest. Conclusion In the automatic bone age assessment of adolescent pelvis, the Inception-ResNet-V2 model performs the best while the Inception-V3 model achieves a similar accuracy as VGG19 model.
Facial reconstruction is a way to recover facial morphology by restoring soft tissues based on unidentified skulls using the knowledge of anatomy, anthropology, aesthetics, and computer science. It is applied in forensic science, oral plastic surgery and archeology, and especially plays an important role in the identification of the origin of the unknown corpses in forensic science. Facial reconstruction is the supplementary means of identification when other approaches (such as DNA comparison, imaging matching, dental records comparison, etc.) cannot identify individual identity. Facial soft tissue thickness (FSTT) is the basis of facial reconstruction and with the development of imaging and computer science, the techniques for measuring FSTT are improving rapidly and many related researches have appeared. This paper summarizes the application of facial reconstruction in forensic science, the accuracy of different methods and the research progress of this field to provide reference to this field.
Facial reconstruction is a way to recover facial morphology by restoring soft tissues based on unidentified skulls using the knowledge of anatomy, anthropology, aesthetics, and computer science.