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A Deep Learning Method for Pediatric Bone Age Estimation using ...


A Deep Learning Method for Pediatric Bone Age Estimation using ...

Background: Accurate bone age assessment is essential for determining the actual degree of development and indicating a disorder in growth.

(PDF) AE-BoNet: A Deep Learning Method for Pediatric Bone Age ...

This study suggests a method for bone age assessment using an unsupervised pre-training approach. Initially, an autoencoder is trained to ...

A Deep Learning Approach to Pediatric Bone Age Assessment ...

A deep learning model trained on pediatric trauma hand radiographs is on par with automated and manual GP-based methods for bone age assessment.

Deep focus approach for accurate bone age estimation from lateral ...

This study aimed to devise a deep-learning approach for accurate bone-age estimation by focusing on the cervical vertebrae on lateral cephalograms of growing ...

A Deep Learning Approach to Pediatric Bone Age Assessment ...

A deep learning model trained on pediatric trauma hand radiographs is on par with automated and manual GP-based methods for bone age assessment ...

A Deep Learning Approach to Pediatric Bone Age Assessment ...

A deep learning model trained on pediatric trauma hand radiographs is on par with automated and manual GP-based methods for bone age assessment and provides ...

Deep learning-based automated bone age estimation for Saudi ...

This study proposes a deep learning-based model utilizing a fully connected convolutional neural network(CNN) to predict bone age from left-hand ...

Pediatric Bone Age Assessment using Deep Learning Models - arXiv

Abstract:Bone age assessment (BAA) is a standard method for determining the age difference between skeletal and chronological age. Manual ...

Bone age assessment based on deep neural networks ... - Frontiers

In this research, we propose a novel two-stage deep learning method for BAA without any manual region annotation, which consists of a cascaded ...

Pediatric Bone Age Assessment using Deep Learning Models

Bone age assessment (BAA) is a standard method for determining the age difference between skeletal and chronological age. Manual processes are complicated ...

Deep Learning Approach for Bone Age Assessment Based on ...

In this paper, we propose a method for bone age assessment that combines a convolutional neural network and a improved TW3-C RUS scoring method.

Bone age assessment using deep learning architecture: A Survey

Abstract: Skeletal bone age evaluation with X-ray pictures is a routine clinical approach for detecting any abnormalities in bone development in children ...

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

The estimation of bone age (BA), which evaluates skeletal maturity, is a valuable tool in assessing children's growth. Usually, it is one of the ...

External validation of deep learning-based bone-age software - Nature

Understanding the current status of skeletal maturity in children is important for evaluating developmental status and in detecting ...

Computerized Bone Age Estimation Using Deep Learning Based ...

MATERIALS AND METHODS. A Greulich-Pyle method–based deep-learning technique was used to develop the automatic software system for bone age ...

An Unsupervised Deep-Learning Method for Bone Age Assessment

The K-means clustering algorithm is used to obtain the final classifications by grouping the latent vectors of the bone images. A set of ...

Attention-based multiple-instance learning for Pediatric bone age ...

Pediatric bone age assessment (BAA) is a common clinical technique for evaluating children's endocrine, genetic, and growth disorders. However, the deep ...

Deep Learning Framework for Automatic Bone Age Assessment

In this work, we propose a fully automated deep learning approach for bone age assessment. The dataset used is from the 2017 Pediatric Bone Age Challenge ...

Paediatric Bone Age Assessment Using Deep Convolutional Neural ...

In this paper, we describe a deep learning approach to the problem of bone age assessment using data from the 2017 Pediatric Bone Age Challenge organized by the ...

Pediatric Bone Age Assessment using Deep Learning Models

Pre-trained models like VGG-16, InceptionV3, XceptionNet, and MobileNet are used to assess the bone age of the input data, and their mean average errors are ...