Literature DB >> 11894888

Computer automated approach to the extraction of epiphyseal regions in hand radiographs.

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

Abstract

Epiphyseal region is the most sensitive region to developmental changes of the skeletal system. Extraction of this area is the very first step in any computerized image analysis. In this report a fully automated analysis of a hand radiograph resulting in extraction of distal and middle regions of the II, III, and IV phalanx is presented. The processing is performed in 3 stages. First, the trend of background is removed from radiograph to obtain a binary hand mask. At this stage a labeling procedure is necessary to eliminate artifacts (markers). Then, II, III, and IV phalanges are identified in the binary image, and the phalangeal axes are drawn. Finally, the intensity profile along each phalangeal axis is analyzed, and, on its basis, distal and middle regions are located. The presented procedure is designed as a part of currently developed system for automatic bone age assessment; however, it also can be as a preprocessing step in other diseases the diagnoses of which may require a computer assistance.

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Year:  2001        PMID: 11894888      PMCID: PMC3452369          DOI: 10.1007/s10278-001-0101-1

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  7 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.  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

3.  The digital atlas of skeletal maturity by Gilsanz and Ratib: a suitable alternative for age estimation of living individuals in criminal proceedings?

Authors:  Sven Schmidt; Inna Nitz; Ronald Schulz; Michael Tsokos; Andreas Schmeling
Journal:  Int J Legal Med       Date:  2009-08-18       Impact factor: 2.686

4.  Bone age assessment of children using a digital hand atlas.

Authors:  Arkadiusz Gertych; Aifeng Zhang; James Sayre; Sylwia Pospiech-Kurkowska; H K Huang
Journal:  Comput Med Imaging Graph       Date:  2007-03-26       Impact factor: 4.790

5.  Racial differences in growth patterns of children assessed on the basis of bone age.

Authors:  Aifeng Zhang; James W Sayre; Linda Vachon; Brent J Liu; H K Huang
Journal:  Radiology       Date:  2008-10-27       Impact factor: 11.105

6.  Automated bone age assessment: motivation, taxonomies, and challenges.

Authors:  Marjan Mansourvar; Maizatul Akmar Ismail; Tutut Herawan; Ram Gopal Raj; Sameem Abdul Kareem; Fariza Hanum Nasaruddin
Journal:  Comput Math Methods Med       Date:  2013-12-16       Impact factor: 2.238

7.  Correlation between Skeletal Age and Metacarpal Bones and Metacarpophalangeal Joints Dimensions.

Authors:  Abdolaziz Haghnegahdar; Hamidreza Pakshir; Ilnaz Ghanbari
Journal:  J Dent (Shiraz)       Date:  2019-09
  7 in total

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