Literature DB >> 11513023

Computer-assisted bone age assessment: image preprocessing and epiphyseal/metaphyseal ROI extraction.

E Pietka1, A Gertych, S Pospiech, F Cao, H K Huang, V Gilsanz.   

Abstract

Clinical assessment of skeletal maturity is based on a visual comparison of a left-hand wrist radiograph with atlas patterns. Using a new digital hand atlas an image analysis methodology is being developed. To assist radiologists in bone age estimation. The analysis starts with a preprocessing function yielding epiphyseal/metaphyseal regions of interest (EMROIs). Then, these regions are subjected to a feature extraction function. Accuracy has been measured independently at three stages of the image analysis: detection of phalangeal tip, extraction of the EMROIs, and location of diameters and lower edge of the EMROIs. Extracted features describe the stage of skeletal development more objectively than visual comparison.

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Year:  2001        PMID: 11513023     DOI: 10.1109/42.938240

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  23 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.  A fuzzy-based growth model with principle component analysis selection for carpal bone-age assessment.

Authors:  Chi-Wen Hsieh; Tzu-Chiang Liu; Tai-Lang Jong; Chui-Mei Tiu
Journal:  Med Biol Eng Comput       Date:  2010-04-20       Impact factor: 2.602

3.  Bone age estimation based on phalanx information with fuzzy constrain of carpals.

Authors:  Chi-Wen Hsieh; Tai-Lang Jong; Chui-Mei Tiu
Journal:  Med Biol Eng Comput       Date:  2007-01-23       Impact factor: 2.602

4.  Automatic bone age assessment for young children from newborn to 7-year-old using carpal bones.

Authors:  Aifeng Zhang; Arkadiusz Gertych; Brent J Liu
Journal:  Comput Med Imaging Graph       Date:  2007-03-21       Impact factor: 4.790

5.  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

6.  Bone age assessment in young children using automatic carpal bone feature extraction and support vector regression.

Authors:  Krit Somkantha; Nipon Theera-Umpon; Sansanee Auephanwiriyakul
Journal:  J Digit Imaging       Date:  2011-12       Impact factor: 4.056

7.  A Deep Automated Skeletal Bone Age Assessment Model with Heterogeneous Features Learning.

Authors:  Chao Tong; Baoyu Liang; Jun Li; Zhigao Zheng
Journal:  J Med Syst       Date:  2018-11-03       Impact factor: 4.460

8.  Black box integration of computer-aided diagnosis into PACS deserves a second chance: results of a usability study concerning bone age assessment.

Authors:  Ina Geldermann; Christoph Grouls; Christiane Kuhl; Thomas M Deserno; Cord Spreckelsen
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

9.  Robust anatomical correspondence detection by hierarchical sparse graph matching.

Authors:  Yanrong Guo; Guorong Wu; Jianguo Jiang; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2012-10-10       Impact factor: 10.048

10.  A Bayesian approach to multistage fitting of the variation of the skeletal age features.

Authors:  Dong Hua; Dechang Chen; Fang Liu; Abdou Youssef
Journal:  J Biomed Biotechnol       Date:  2009-06-04
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