Bone age assessment has always been one of the key issues and difficulties in forensic science. With the gradual development of machine learning in many industries, it has been widely introduced to imageology, genomics, oncology, pathology, surgery and other medical research fields in recent years. The reason why the above research fields can be closely combined with machine learning, is because the research subjects of the above branches of medicine belong to the computer vision category. Machine learning provides unique advantages for computer vision research and has made breakthroughs in medical image recognition. Based on the advantages of machine learning in image recognition, it was combined with bone age assessment research, in order to construct a recognition model suitable for forensic skeletal images. This paper reviews the research progress in bone age assessment made by scholars at home and abroad using machine learning technology in recent years.
Age Determination by Skeleton ; Humans ; Machine Learning

Bone age is an important indicator of human growth and development, which can objectively reflect the growth level and maturity of individuals. Traditional manual bone age assessment usually compares the X-ray of the left wrist with the reference standard to obtain the corresponding bone age. This method is time-consuming and its results vary with different observers. In recent years, with the continuous development of computer science, bone age assessment has began to change from traditional manual assessment to automatic assessment. Although there has already been numerous researches on automatic bone age assessment, most of them are still in the experimental stage. This paper reviews related research and progress on automatic bone age assessment at home and abroad in recent years, in order to provide reference and research ideas for relevant researchers.
Age Determination by Skeleton ; Humans ; Wrist ; X-Rays

The main methods of age estimation at present mostly rely on characteristic physical and chemical changes of skeleton, soft tissue, cells, biomacromolecules and the other substances. Because physiological changes of tissues and organs during growth are extremely complicated, all methods have their limitations. In practical, it is necessary to combine several methods together in order to improve the accuracy of age estimation. This article reviewed recent development on age estimation domestically and abroad and discussed advantage and disadvantage of different methods.
Age Determination by Skeleton ; Age Determination by Teeth ; DNA/genetics* ; Forensic Anthropology/methods* ; Humans

PURPOSE: This study compared bone ages measured by the Greulich-Pyle (GP) and Tanner-Whitehouse 3 (TW3 ) methods and investigated the differences in predicted adult heights measured by Bayley-Pinneau (BP) and TW3 methods. METHODS: Bone ages were assessed from left-wrist radiographs by two investigators, one for each GP and TW3 methods in 85 normal children, 30 precocious puberty girls, and 30 constitutional growth delay boys. The differences between the measured predicted adult heights using the BP and TW3 methods were compared in each group. RESULTS: The bone age measured by the TW3 method was less than that by the GP method in normal children. The predicted adult heights measured by the two methods showed no significant difference in normal boys, while the predicted adult height measured by the TW3 method was higher than that by the BP method for normal girls (156.4+/-4.7 cm vs. 158.9+/-3.8 cm, P<0.01) and for precocious puberty girls (156.3+/-4.0 cm vs. 159.3+/-4.2 cm, P<0.01). In contrast, the predicted adult height was higher from the BP method than from the TW3 method in constitutional growth delay boys (173.3+/-4.4 cm vs. 169.7+/-3.2 cm, P<0.01). CONCLUSION: There were significant differences in predicted adult heights between the BP and TW3 method in normal girls, precocious puberty girls, or constitutional growth delay boys. In precocious puberty and constitutional growth delay, the BP method might be preferred to predict adult height, but further studies on final adult height are needed.
Adult ; Age Determination by Skeleton ; Child ; Humans ; Puberty, Precocious ; Research Personnel

OBJECTIVEThe device of a bone age film of analysis and process was designed, can calculate the expected patient's height and identify growth level and development.

METHODSSelect the DR bone age of 100 children of 6-13 years old, used semi Lagrange algorithm of target region of interest on bone age piece (ROI) for image analysis, compared with 2 pediatric endocrinologists (A, B) who used TW3 artificial to judge bone age (two methods were detected 2 times), and report the results.

RESULTSBone age assessment process, forecast error of bone age reduced to 0.12 years.

CONCLUSIONSThis device can quickly calculate the expected patient's height and identify his growth level, improve the speed and accuracy of bone age assessment, especially in the poor medical conditions in rural and remote areas.

No abstract available.
Palatal Expansion Technique ; Age Determination by Skeleton ; Orthodontic Appliances

Individual identification based on imaging data of the skeleton of a corpse is a key technique for forensic identification. To reduce the influence of artificial factors, computer-aided semi-automatic or automatic individual identification has become one of the research directions of skeleton-based individual identification in forensic radiology. Therefore, this paper reviews and summarizes literatures related to estimation of anthropological information such as, age and sex by computer-aided forensic radiology bone characteristics and individual identification based on bone imaging characteristics, in order to provide reference on skeleton-based individual identification in forensic radiology.
Age Determination by Skeleton ; Bone and Bones ; Computers ; Forensic Anthropology ; Radiology

Individual identification by measuring the human skeleton is an important research in the field of forensic anthropology. Computed tomography （CT） technology can provide high-resolution image of skeleton. Skeleton image can be reformed by software in the post-processing workstation. Different skeleton measurement indexes of anthropology, such as diameter, angle, area and volume, can be measured on section and reformative images. Measurement process is barely affected by human factors. This paper reviews the literatures at home and abroad about the application of measuring skeleton by CT in forensic anthropology research for individual identification in four aspects, including sex determination, height infer, facial soft tissue thickness measurement and age estimation. The major technology and the application of CT in forensic anthropology research are compared and discussed, respectively.
Age Determination by Skeleton ; Bone and Bones/diagnostic imaging* ; Forensic Anthropology/trends* ; Humans ; Sex Determination Analysis ; Software ; Tomography, X-Ray Computed/methods*

Burned bones have their unique characteristics in investigation of fire disaster/crimes, airplane disaster, explosion and other accidents. To study the morphological changes of skeletal tissue and DNA changes at different incinerating temperature might provide precise standard means to determine genera, sex, and age. Genetic locus was also applied in the above fields. The techniques to extract and detect of DNA in burning bones have been improved in recent years. In this article investigation advancement of analysis of burned bones with the morphology, histology, and molecular biology as well as the latest methods and techniques were reviewed. These results provide a new approach for further research and practice in forensic medicine.
Age Determination by Skeleton/methods* ; Animals ; Bone and Bones/pathology* ; Burns/pathology* ; DNA/analysis* ; Forensic Anthropology/methods* ; Hot Temperature ; Humans ; Sex Determination by Skeleton/methods* ; Tandem Repeat Sequences ; Time Factors

BACKGROUND: Bone age measurements have clinical significance in estimation of growth status and prediction of final adult height. Mostly used methods of bone age measurements are Tanner Whitehouse method(TW2) and Greulich-Pyle method(OP). TW2 is known to be more accurate method in determining the bone age, compared to GP. But GP is being used more widely despite some shortcomings, because TW2 is time consuming and need special training. In this study, we observed the correlation between GP and TW2 to evaluate which bone age among three portions of hand and wrist[metacarpals and phalanges(GP1), carpal bones(GP2), distai radius and ulna (GP3)], measured by GP, was more correlated with the bone age, measured by TW2. METHODS: Left hand/wrist radiographs were taken from 100 prepubertal children with normal growth. These radiogrphs were reviewed by two pediatric endocrinologists independently. Bone ages using TW2 were measured at first, and then GP1, GP2, and GP3 were measured. These bone ages had been compared with TW2, using SAS computer program. RESULTS: The mean chronological age of 100 children was 10.0+/-2.5 years(5 years to 14.7 years range, 63 males and 37 females). The bone age by TW2 was 9.0+/- 2.6 years(2.3 to 13.6 years). The bone age by GP1, GP2, and GP3 were 8.8+/-2.5 years, 8.7+/-2.9 years, and 8.3+/-2.8 years, respectively. Bone ages by TW2 were significantly closer to the chronological age than those by GP. The Pea~rson correlation coefficients of GP1, GP2, and GP3 in eomparison to TW2 were 0,87(p=0.0001), 0.94(p=0.0001), and 0.91(p=0.0001), respectively, There are significant correlatkm between bone ages by TW2 and GP. Bone ages by GP2 and GP3 were statistically significantly different from those by TW2(P<0.01). Bone ages by GP1 has no statistical difference with that by TW2(P=0.64). CONCLUSION: TW2 method is more accurate than GP method in determining the bone age, but it needs time-consuming and laborious efforts. We suggest that the use of GP method for the metacarpals and phalanges can result in a considerable saving of time with no significant loss of accuracy and reproducibility.
Adult ; Age Determination by Skeleton ; Child ; Hand ; Humans ; Male ; Metacarpal Bones ; Radius ; Ulna