Literature DB >> 8061759

Automatic bone age measurement using computerized image analysis.

J M Tanner1, R D Gibbons.   

Abstract

In 1992 we described a computer-assisted method for assigning Tanner-Whitehouse RUS skeletal maturity scores to hand-wrist radiographs. An operator positions each epiphysis in turn beneath a video camera, views the image on the computer screen and corrects the position of the radiograph by matching to templates of the TW stages displayed on the screen. The process is then automatic; the computer, not the operator, rates the bone. The image is digitized and then represented by a large number of mathematical coefficients. These coefficients are then compared to those generated by each stage of the TW standards, and the closest match is sought. Since the comparison is quantitative the system produces continuous stage scores instead of the old discrete ones such as B, C, D, etc. Thus in longitudinal data a much smoother progression of skeletal maturity scores with age is achieved. The reliability of the computer-assisted skeletal age score (CASAS) is considerably greater than that of the usual manual method. Differences between duplicate readings of a bone by a single observer average about 0.25 stage, and reach 1.0 stage or more only in about 3% of instances, compared with 15-20% characteristic of manual ratings.

Mesh:

Year:  1994        PMID: 8061759     DOI: 10.1515/jpem.1994.7.2.141

Source DB:  PubMed          Journal:  J Pediatr Endocrinol


  9 in total

1.  Computer-assisted bone age assessment: graphical user interface for image processing and comparison.

Authors:  Ewa Pietka; Arkadiusz Gertych; Sylwia Pospiechâ Euro Kurkowska; Fei Cao; H K Huang; Vincente Gilzanz
Journal:  J Digit Imaging       Date:  2004-06-04       Impact factor: 4.056

2.  Web-based bone age assessment by content-based image retrieval for case-based reasoning.

Authors:  Benedikt Fischer; Petra Welter; Rolf W Günther; Thomas M Deserno
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-06-14       Impact factor: 2.924

3.  Implementation and statistical evaluation of a web-based software for bone age assessment.

Authors:  Metin Yildiz; Albert Guvenis; Esra Guven; Didar Talat; Mahmut Haktan
Journal:  J Med Syst       Date:  2010-02-02       Impact factor: 4.460

4.  Forensic bone age estimation of adolescent pelvis X-rays based on two-stage convolutional neural network.

Authors:  Li-Qin Peng; Yu-Cheng Guo; Lei Wan; Tai-Ang Liu; Peng Wang; Hu Zhao; Ya-Hui Wang
Journal:  Int J Legal Med       Date:  2022-01-18       Impact factor: 2.686

5.  An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA).

Authors:  Hum Yan Chai; Lai Khin Wee; Tan Tian Swee; Sh-Hussain Salleh; Lim Yee Chea
Journal:  Biomed Eng Online       Date:  2011-09-28       Impact factor: 2.819

Review 6.  Adolescent health and the environment.

Authors:  M S Golub
Journal:  Environ Health Perspect       Date:  2000-04       Impact factor: 9.031

7.  Fully Automated Deep Learning System for Bone Age Assessment.

Authors:  Hyunkwang Lee; Shahein Tajmir; Jenny Lee; Maurice Zissen; Bethel Ayele Yeshiwas; Tarik K Alkasab; Garry Choy; Synho Do
Journal:  J Digit Imaging       Date:  2017-08       Impact factor: 4.056

Review 8.  Multipurpose contrast enhancement on epiphyseal plates and ossification centers for bone age assessment.

Authors:  Hum Yan Chai; Tan Tian Swee; Gan Hong Seng; Lai Khin Wee
Journal:  Biomed Eng Online       Date:  2013-04-08       Impact factor: 2.819

9.  Bone age: assessment methods and clinical applications.

Authors:  Mari Satoh
Journal:  Clin Pediatr Endocrinol       Date:  2015-10-24
  9 in total

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