- Attention|based multiple|instance learning for Pediatric bone age ...🔍
- Multi|Branch Attention Learning for Bone Age Assessment with ...🔍
- Attention|Based Multiscale Localization for Bone Age Assessment🔍
- Bone age assessment by multi|granularity and multi|attention ...🔍
- Learning Rich Attention for Pediatric Bone Age Assessment🔍
- Bone age assessment with various machine learning techniques🔍
- Assessment of Bone Age Based on Hand Radiographs Using ...🔍
- A Deep Learning Approach to Pediatric Bone Age Assessment ...🔍
Attention|based multiple|instance learning for Pediatric bone age ...
Attention-based multiple-instance learning for Pediatric bone age ...
A novel method for high performance and interpretable bone age prediction without additional manual annotations has been developed.
Multi-Branch Attention Learning for Bone Age Assessment with ...
[20] proposed a specific identity labels-based bone age assessment (SIMBA) model, which involved the gender as well as the age of patients.
Attention-Based Multiscale Localization for Bone Age Assessment
Abstract: Bone Age Assessment (BAA) is crucial for the biological maturity evaluation of children. Developing automated techniques of BAA has gained a lot ...
Attention-based multiple-instance learning for Pediatric bone age ...
Attention-based multiple-instance learning for Pediatric bone age assessment with efficient and interpretable · List of references · Publications that cite this ...
Bone age assessment by multi-granularity and multi-attention ... - NCBI
... bone through transfer learning, and bone age calculation based on the percentile curve of bone maturity. The MAE reached 0.61 years on the data set and had ...
Multi-Branch Attention Learning for Bone Age Assessment with ...
Bone age assessment (BAA) is a typical clinical technique for diagnosing endocrine and metabolic diseases in children's development.
Learning Rich Attention for Pediatric Bone Age Assessment
Bone Age Assessment (BAA) is a challenging clinical practice in pediatrics, which requires rich attention on multiple anatomical Regions of ...
Bone age assessment with various machine learning techniques
The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis ...
Assessment of Bone Age Based on Hand Radiographs Using ...
(1) Objective: In this study, a regression-based multi-modal deep learning model was developed for use in bone age assessment (BAA) utilizing hand ...
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.
Attention-Guided Discriminative Region Localization and Label ...
metabolic disorders during child development. Existing deep learning based methods for classifying bone age use the global image as input ...
Bone age estimation using deep learning and hand X-ray images ...
A multiple instance learning based method for bone age prediction using whole-body bone scan images that combines attention-based multiple instances learning ...
Positional Multi-Cross-Attention for Bone Age Estimation Using ...
Attention-based multiple-instance learning for Pediatric bone age assessment with efficient and interpretable. Chong Wang, Yang Wu, Chen Wang ...
Bone Age Assessment Based on Deep Convolutional Features and ...
Finally, to realize the fast computation speed and feature interaction, this paper proposes to use an extreme learning machine algorithm as the ...
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 ...
Deep Learning Approach for Bone Age Assessment Based on ...
The method first uses a convolutional neural network to output a probability value for the predicted level of each epiphyseal region. Next, ...
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 ...
[PDF] Bone age assessment with various machine learning techniques
The goal of this paper is to present the state of the art evidence, trends and gaps in the research related to bone age assessment studies that make use of ...
Ridge Regression Neural Network for Pediatric Bone Age Assessment
In the second stage, we design a regression neural network architecture composed of a pre-trained convolutional neural network for learning ...
Frontiers | Bone Age Assessment Based on Deep Convolutional ...
Bone age is an important metric to monitor children's skeleton development in pediatrics. As the development of deep learning DL-based bone ...