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Age Determination by Skeleton

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Use of artificial intelligence in determination of bone age of the healthy individuals: A scoping review.

Journal of the World federation of orthodontists
BACKGROUND: Bone age assessment, as an indicator of biological age, is widely used in orthodontics and pediatric endocrinology. Owing to significant subject variations in the manual method of assessment, artificial intelligence (AI), machine learning...

Deeplasia: deep learning for bone age assessment validated on skeletal dysplasias.

Pediatric radiology
BACKGROUND: Skeletal dysplasias collectively affect a large number of patients worldwide. Most of these disorders cause growth anomalies. Hence, evaluating skeletal maturity via the determination of bone age (BA) is a useful tool. Moreover, consecuti...

Machine learning and deep learning enabled age estimation on medial clavicle CT images.

International journal of legal medicine
The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the perf...

Automated bone age assessment in a German pediatric cohort: agreement between an artificial intelligence software and the manual Greulich and Pyle method.

European radiology
OBJECTIVES: This study aimed to evaluate the performance of artificial intelligence (AI) software in bone age (BA) assessment, according to the Greulich and Pyle (G&P) method in a German pediatric cohort.

Applicability and robustness of an artificial intelligence-based assessment for Greulich and Pyle bone age in a German cohort.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
PURPOSE: The determination of bone age (BA) based on the hand and wrist, using the 70-year-old Greulich and Pyle (G&P) atlas, remains a widely employed practice in various institutions today. However, a more recent approach utilizing artificial intel...

Radiological age assessment based on clavicle ossification in CT: enhanced accuracy through deep learning.

International journal of legal medicine
BACKGROUND: Radiological age assessment using reference studies is inherently limited in accuracy due to a finite number of assignable skeletal maturation stages. To overcome this limitation, we present a deep learning approach for continuous age ass...

Determination of growth and developmental stages in hand-wrist radiographs : Can fractal analysis in combination with artificial intelligence be used?

Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie
PURPOSE: The goal of this work was to assess the classification of maturation stage using artificial intelligence (AI) classifiers.

Age and sex estimation in cephalometric radiographs based on multitask convolutional neural networks.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: Age and sex characteristics are evident in cephalometric radiographs (CRs), yet their accurate estimation remains challenging due to the complexity of these images. This study aimed to harness deep learning to automate age and sex estimat...

Development of a deep-learning algorithm for age estimation on CT images of the vertebral column.

Legal medicine (Tokyo, Japan)
PURPOSE: The accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on C...

Evaluating the Robustness of a Deep Learning Bone Age Algorithm to Clinical Image Variation Using Computational Stress Testing.

Radiology. Artificial intelligence
Purpose To evaluate the robustness of an award-winning bone age deep learning (DL) model to extensive variations in image appearance. Materials and Methods In December 2021, the DL bone age model that won the 2017 RSNA Pediatric Bone Age Challenge wa...