AIMC Topic: Hand Bones

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Traditional and New Methods of Bone Age Assessment-An Overview.

Journal of clinical research in pediatric endocrinology Oct 26, 2020
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...
Neural Networks, Computer Female Infant, Newborn Humans Infant Diagnosis, Computer-Assisted Deep Learning Adolescent Reproducibility of Results Young Adult Male Automation Child Development Wrist Joint Child, Preschool Hand Bones Child Age Factors Age Determination by Skeleton Adolescent Development Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Observer Variation
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Skeletal bone age prediction based on a deep residual network with spatial transformer.

Computer methods and programs in biomedicine Sep 12, 2020
OBJECTIVE: Bone age prediction can be performed by medical experts manually assessment of X-ray images of the hand bone. In practice, the workload is huge, resource consumption is large, measurement takes a long time, and it is easily influenced by h...
Image Processing, Computer-Assisted Hand Bones Machine Learning Algorithms Humans Neural Networks, Computer
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Automated age estimation from MRI volumes of the hand.

Medical image analysis Jul 31, 2019
Highly relevant for both clinical and legal medicine applications, the established radiological methods for estimating unknown age in children and adolescents are based on visual examination of bone ossification in X-ray images of the hand. Our group...
Datasets as Topic Age Determination by Skeleton Hand Bones Child Imaging, Three-Dimensional Magnetic Resonance Imaging Humans Machine Learning Adolescent
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The RSNA Pediatric Bone Age Machine Learning Challenge.

Radiology Nov 27, 2018
Purpose The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challenge was created to show an application of machine learning (ML) and artificial intelligence (AI) in medical imaging, promote collaboration to catalyze ...
Female Male Child Age Determination by Skeleton Radiography Hand Bones Humans Machine Learning Image Interpretation, Computer-Assisted Algorithms Databases, Factual
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Regression Convolutional Neural Network for Automated Pediatric Bone Age Assessment From Hand Radiograph.

IEEE journal of biomedical and health informatics Oct 19, 2018
Skeletal bone age assessment is a common clinical practice to investigate endocrinology, and genetic and growth disorders of children. However, clinical interpretation and bone age analyses are time-consuming, labor intensive, and often subject to in...
Tomography, X-Ray Computed Female Male Child Image Interpretation, Computer-Assisted Deep Learning Adolescent Humans Neural Networks, Computer Child Development Databases, Factual Hand Bones
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Automatic Age Estimation and Majority Age Classification From Multi-Factorial MRI Data.

IEEE journal of biomedical and health informatics Sep 24, 2018
Age estimation from radiologic data is an important topic both in clinical medicine as well as in forensic applications, where it is used to assess unknown chronological age or to discriminate minors from adults. In this paper, we propose an automati...
Humans Neural Networks, Computer Female Age Determination by Skeleton Adolescent Image Interpretation, Computer-Assisted Hand Bones Young Adult Magnetic Resonance Imaging Clavicle Tooth Adult Male
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An X-ray bone age assessment method for hands and wrists of adolescents in Western China based on feature fusion deep learning models.

International journal of legal medicine Sep 1, 2025
The epiphyses of the hand and wrist serve as crucial indicators for assessing skeletal maturity in adolescents. This study aimed to develop a deep learning (DL) model for bone age (BA) assessment using hand and wrist X-ray images, addressing the chal...
Male Deep Learning China Adolescent Retrospective Studies Hand Humans Child Female Epiphyses Age Determination by Skeleton Radiography Young Adult Hand Bones Wrist
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Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Bone age is an essential measure of skeletal maturity in children with growth disorders. It is typically assessed by a trained physician using radiographs of the hand and a reference model. However, it has been described that the reference models lea...
Deep Learning Adolescent Child, Preschool Normal Distribution Image Interpretation, Computer-Assisted Infant, Newborn Humans Observer Variation Age Determination by Skeleton Retrospective Studies Young Adult Child Hand Bones Female Infant Radiography
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