Literature DB >> 30119064

Evaluation of a Computer-Aided Diagnosis System for Automated Bone Age Assessment in Comparison to the Greulich-Pyle Atlas Method: A Multireader Study.

Christian Booz1, Julian L Wichmann1, Sabine Boettger1, Ahmed Al Kamali1, Simon S Martin1, Lukas Lenga1, Doris Leithner1, Moritz H Albrecht1, Hanns Ackermann2, Thomas J Vogl1, Boris Bodelle1, Benjamin Kaltenbach1.   

Abstract

OBJECTIVE: The aim of this study was to investigate a novel version of a computer-aided diagnosis (CAD) system developed for automated bone age (BA) assessment in comparison to the Greulich and Pyle method, regarding its accuracy and the influence of carpal bones on BA assessment.
METHODS: Total BA, BA of the left distal radius, and BA of carpal bones in 305 patients were determined independently by 3 blinded radiologists and assessed by the CAD system. Pearson product-moment correlation, Bland-Altman plot, root-mean-square deviation, and further agreement analyses were computed.
RESULTS: Mean total BA and BA of the distal radius showed high correlation between both approaches (r = 0.985 and r = 0.963). There was significantly higher correlation between values of total BA and BA of the distal radius (r = 0.969) compared with values of total BA and BA of carpal bones (r = 0.923). The assessment of carpal bones showed significantly lower interreader agreement compared with measurements of the distal radius (κ = 0.79 vs κ = 0.98).
CONCLUSION: A novel version of a CAD system enables highly accurate automated BA assessment. The assessment of carpal bones revealed lower precision and interreader agreement. Therefore, methods determining BA without analyzing carpal bones may be more precise and accurate.

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Year:  2019        PMID: 30119064     DOI: 10.1097/RCT.0000000000000786

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   2.081


  4 in total

1.  Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development.

Authors:  Fengdan Wang; Xiao Gu; Shi Chen; Yongliang Liu; Qing Shen; Hui Pan; Lei Shi; Zhengyu Jin
Journal:  PeerJ       Date:  2020-04-01       Impact factor: 2.984

2.  Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method.

Authors:  Christian Booz; Ibrahim Yel; Julian L Wichmann; Sabine Boettger; Ahmed Al Kamali; Moritz H Albrecht; Simon S Martin; Lukas Lenga; Nicole A Huizinga; Tommaso D'Angelo; Marco Cavallaro; Thomas J Vogl; Boris Bodelle
Journal:  Eur Radiol Exp       Date:  2020-01-28

3.  Ensemble Learning with Multiclassifiers on Pediatric Hand Radiograph Segmentation for Bone Age Assessment.

Authors:  Rui Liu; Yuanyuan Jia; Xiangqian He; Zhe Li; Jinhua Cai; Hao Li; Xiao Yang
Journal:  Int J Biomed Imaging       Date:  2020-10-27

4.  Associations between prenatal serum levels of leptin, IGF-I, and estradiol and adolescent mothers' height gain during and after pregnancy.

Authors:  Reyna Sámano; Hugo Martínez-Rojano; Gabriela Chico-Barba; María Hernández-Trejo; Raymundo Guzmán; Gabriel Arteaga-Troncoso; Mariana Alejandra Figueroa-Pérez; Rosa María Morales; Gabriela Martínez
Journal:  PLoS One       Date:  2020-02-11       Impact factor: 3.240

  4 in total

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