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Published in 2019 at "Pediatric Radiology"
DOI: 10.1007/s00247-019-04587-y
Abstract: Background Recently developed convolutional neural network (CNN) models determine bone age more accurately than radiologists. Objective The purpose of this study was to determine whether a CNN and radiologists can accurately predict bone age from…
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Keywords:
age;
index finger;
bone age;
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Published in 2022 at "Pediatric Radiology"
DOI: 10.1007/s00247-022-05295-w
Abstract: The autonomous artificial intelligence (AI) system for bone age rating (BoneXpert) was designed to be used in clinical radiology practice as an AI-replace tool, replacing the radiologist completely. The aim of this study was to…
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Keywords:
radiology;
bonexpert;
autonomous artificial;
bone age ... See more keywords
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Published in 2019 at "European Radiology"
DOI: 10.1007/s00330-019-06300-x
Abstract: Objectives To assess the effect of secular change on skeletal maturation and thus on the applicability of the Greulich and Pyle (G&P) and Tanner and Whitehouse (TW3) methods. Methods BoneXpert was used to assess bone…
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Keywords:
twenty first;
age;
first century;
bone age ... See more keywords
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Published in 2018 at "Journal of Digital Imaging"
DOI: 10.1007/s10278-018-0053-3
Abstract: Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized method for assessment of BAA is the Greulich and Pyle method (Pediatr Radiol 46.9:1269–1274,…
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Keywords:
network;
bone age;
age;
deep learning ... See more keywords
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Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-08943-1
Abstract: Bone age assessment is a pediatric examination that determines the difference between skeletal age and chronological age. The discrepancy between the two ages will often trigger the likelihood of genetic disorders, hormonal complications and abnormalities…
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Keywords:
age;
age assessment;
fusion learning;
bone age ... See more keywords
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Published in 2017 at "Medical Image Analysis"
DOI: 10.1016/j.media.2016.10.010
Abstract: HIGHLIGHTSTesting several Convolutional Neural Networks on for skeletal bone age assessment with X‐Ray images.BoNet: a CNN for automated skeletal age assessment able to cope with hand nonrigid deformation.First automated skeletal bone age assessment work tested…
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Keywords:
age assessment;
age;
skeletal bone;
deep learning ... See more keywords
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Published in 2020 at "Medical image analysis"
DOI: 10.1016/j.media.2020.101743
Abstract: Pediatric endocrinologists regularly order radiographs of the left hand to estimate the degree of bone maturation in order to assess their patients for advanced or delayed growth, physical development, and to monitor consecutive therapeutic measures.…
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Keywords:
mimicking radiologists;
hand;
bone;
radiologists workflow ... See more keywords
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Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-90157-y
Abstract: Understanding how a neural network makes decisions holds significant value for users. For this reason, gradient-based saliency mapping was tested on an artificial intelligence (AI) regression model for determining hand bone age from X-ray radiographs.…
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Keywords:
saliency;
age;
gradient based;
model ... See more keywords
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Published in 2022 at "Scientific Reports"
DOI: 10.1038/s41598-022-05282-z
Abstract: Artificial intelligence (AI) is increasingly being used in bone-age (BA) assessment due to its complicated and lengthy nature. We aimed to evaluate the clinical performance of a commercially available deep learning (DL)–based software for BA…
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Keywords:
age;
deep learning;
bone age;
software ... See more keywords
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Published in 2022 at "Journal of Pediatric Orthopaedics"
DOI: 10.1097/bpo.0000000000002269
Abstract: Background: Radiographic assessment of bone age is critically important to decision-making on the type and timing of operative interventions in pediatric orthopaedics. The current widely accepted method for determining bone age is time and resource-intensive.…
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Keywords:
bone age;
abbreviated methods;
reliability;
age ... See more keywords
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Published in 2023 at "Journal of Pediatric Orthopaedics"
DOI: 10.1097/bpo.0000000000002368
Abstract: Background: The concept of delayed skeletal maturity in Legg-Calve-Perthes Disease (LCPD) has been well identified with the Greulich and Pyle (GP) atlas showing 1 to 2 years delay. Recently the optimized Oxford hip skeletal age…
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Keywords:
bone age;
skeletal maturity;
age;
maturity ... See more keywords