[Age assessment using CT of knee joint and neural network technologies]. / Otsenka vozrasta s ispol'zovaniem KT kolennogo sustava i neirosetevykh tekhnologii.

Age assessment of living persons plays an important role in clinical and sports medicine, as well as in law practice. Traditional methods have a number of problems: age restrictions, technical difficulties of visualization, low reproducibility and subjectivity of estimation. The proposed approach, which implies the use of multispiral computed tomography (MSCT) and database mining, will eliminate these drawbacks and improve the estimation of age. The aim of the study was to investigate the use of deep learning algorithms to classify the age groups (with a threshold level of 18 years) for CT images of knee joint. The study included 455 MSCT images of the knee joint of male and female subjects aged from 13 to 24. The method included score assessment of the distal femur's epiphyseal synostosis stages, tibia and fibula proximal epiphyses and a preliminary statistical analysis of correlations between age and stages of synostosis. The challenge of binary classification of target age groups with the use of convolutional neural networks was implemented at the second phase of the trial. Various architectures of convolutional neural networks and their ensembles were tested. The result of the study showed that the total score of epiphyseal synostosis has the highest correlation with the age (r=0.88). The proposed method of chronological age assessment on the basis of the knee area CT images research using deep learning algorithms demonstrated a good result. The classification accuracy (threshold level of 18 years) was 0.86.

[Age prediction based on the examination of bone tissue elemental composition using energy dispersive X-Ray spectroscopy]. / Prognozirovanie vozrasta na osnovanii izucheniya elementnogo sostava kostnoi tkani s pomoshch'yu energodispersionnoi rentgenovskoi spektroskopii.

THE AIM OF THE STUDY: Was to assess the possibility of using chemical analysis of bone mineral content by the means of an energy dispersive X-Ray spectroscopy to determine the age of unidentified corpses for forensic identification. A semi-quantative chemical microanalysis of bone fragments of 85 male and female corpses aged between 21 and 91 was done through the use of energy dispersive X-Ray spectrometer. The association of bone tissue apatite mineral composition with age is confirmed and a formula, connecting age and chemical composition change, is proposed. The possibility of using quantitive evaluation of chemical elements content in the normative mineral to determine the unidentified corpse's age in a standard laboratory, equipped with an energy dispersive X-Ray spectrometer, was proved.