AIMC Topic: Age Determination by Skeleton
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The psc-CVM assessment system: A three-stage type system for CVM assessment based on deep learning.
BMC oral health
Aug 12, 2023
BACKGROUND: Many scholars have proven cervical vertebral maturation (CVM) method can predict the growth and development and assist in choosing the best time for treatment. However, assessing CVM is a complex process. The experience and seniority of t...
High performance for bone age estimation with an artificial intelligence solution.
Diagnostic and interventional imaging
Apr 22, 2023
PURPOSE: The purpose of this study was to compare the performance of an artificial intelligence (AI) solution to that of a senior general radiologist for bone age assessment.
Prediction of Fishman's skeletal maturity indicators using artificial intelligence.
Scientific reports
Apr 11, 2023
The present study aimed to evaluate the performance of automated skeletal maturation assessment system for Fishman's skeletal maturity indicators (SMI) for the use in dental fields. Skeletal maturity is particularly important in orthodontics for the ...
A real-time automated bone age assessment system based on the RUS-CHN method.
Frontiers in endocrinology
Mar 15, 2023
BACKGROUND: Bone age is the age of skeletal development and is a direct indicator of physical growth and development in children. Most bone age assessment (BAA) systems use direct regression with the entire hand bone map or first segmenting the regio...
Combined assisted bone age assessment and adult height prediction methods in Chinese girls with early puberty: analysis of three artificial intelligence systems.
Pediatric radiology
Dec 28, 2022
BACKGROUND: The applicability and accuracy of artificial intelligence (AI)-assisted bone age assessment and adult height prediction methods in girls with early puberty are unknown.
The uncovered biases and errors in clinical determination of bone age by using deep learning models.
European radiology
Dec 20, 2022
OBJECTIVES: To evaluate AI biases and errors in estimating bone age (BA) by comparing AI and radiologists' clinical determinations of BA.
iCVM: An Interpretable Deep Learning Model for CVM Assessment Under Label Uncertainty.
IEEE journal of biomedical and health informatics
Aug 11, 2022
The Cervical Vertebral Maturation (CVM) method aims to determine the craniofacial skeletal maturational stage, which is crucial for orthodontic and orthopedic treatment. In this paper, we explore the potential of deep learning for automatic CVM asses...
A novel approach to radiographic detection of growth development period with hand-wrist radiographs: A preliminary study with ImageJ imaging software.
Orthodontics & craniofacial research
May 20, 2022
OBJECTIVE: The purpose of this study is to determine whether or not the ImageJ program can be used to automatically determine the growth period of the hand and wrist which have different growth-development periods according to the density values in t...
Construction of artificial intelligence system of carpal bone age for Chinese children based on China-05 standard.
Medical physics
Mar 1, 2022
PURPOSE: The purpose of this study is to construct an automatic carpal bone age evaluation system for Chinese children based on TW3-C Carpal method by deep learning and to evaluate the accuracies in test set and clinical test set.
Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment.
Pediatric radiology
Feb 28, 2022
BACKGROUND: 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.
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