Literature DB >> 21671096

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

Benedikt Fischer1, Petra Welter, Rolf W Günther, Thomas M Deserno.   

Abstract

PURPOSE: Maturity estimation by radiological bone age assessment (BAA) is a frequent task for pediatric radiologists. Following Greulich and Pyle, all hand bones are compared with a standard atlas, or a subset of bones is examined according to Tanner and Whitehouse. We support BAA comparing the epiphyses of a current case to similar cases with validated bone age by content-based image retrieval (CBIR).
METHODS: A web-based prototype case-based retrieval system for BAA was developed and is publicly available. Hand radiographs from the USC database or user uploads may be retrieved by image-based query. The ten best matching cases for each epiphysis are retrieved by CBIR and displayed with their BAA, similarity score, and the derived age estimate. The similarity is approximated by cross-correlation. The USC hand database includes 1,101 cases comprising four ethnic groups of both genders between zero and 18 years of chronological age with radiographs and two annotated BAA. The USC image data have been enriched by marking the epiphyseal centers between metacarpals and distal phalanges.
RESULTS: Leave-one-out experiments yielded a mean error rate of 0.99 years and a standard deviation of 0.76 years in comparison with the mean USC-BAA. The research prototype enables radiologists to judge their agreement based on similarity of retrieved cases and the derived age.
CONCLUSIONS: CBIR provides support to the radiologist with a second opinion for BAA. Self-explanatory web applications can be established to support workflow integration. Enhancements in similarity computation and interface usability may further improve the system.

Mesh:

Year:  2011        PMID: 21671096     DOI: 10.1007/s11548-011-0627-8

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  12 in total

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

Authors:  E Pietka; A Gertych; S Pospiech; F Cao; H K Huang; V Gilsanz
Journal:  IEEE Trans Med Imaging       Date:  2001-08       Impact factor: 10.048

2.  Content-based image retrieval in medical applications.

Authors:  T M Lehmann; M O Güld; C Thies; B Fischer; K Spitzer; D Keysers; H Ney; M Kohnen; H Schubert; B B Wein
Journal:  Methods Inf Med       Date:  2004       Impact factor: 2.176

3.  Use of diagnostic decision support systems in medical education.

Authors:  E S Berner; J J McGowan
Journal:  Methods Inf Med       Date:  2010-04-20       Impact factor: 2.176

4.  Workflow management of content-based image retrieval for CAD support in PACS environments based on IHE.

Authors:  Petra Welter; Christian Hocken; Thomas M Deserno; Christoph Grouls; Rolf W Günther
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-04-09       Impact factor: 2.924

5.  A generic concept for the implementation of medical image retrieval systems.

Authors:  Mark O Güld; Christian Thies; Benedikt Fischer; Thomas M Lehmann
Journal:  Int J Med Inform       Date:  2007 Feb-Mar       Impact factor: 4.046

6.  Extended query refinement for medical image retrieval.

Authors:  Thomas M Deserno; Mark O Güld; Bartosz Plodowski; Klaus Spitzer; Berthold B Wein; Henning Schubert; Hermann Ney; Thomas Seidl
Journal:  J Digit Imaging       Date:  2007-05-12       Impact factor: 4.056

7.  Ontology of gaps in content-based image retrieval.

Authors:  Thomas M Deserno; Sameer Antani; Rodney Long
Journal:  J Digit Imaging       Date:  2008-02-01       Impact factor: 4.056

Review 8.  Automatic bone age measurement using computerized image analysis.

Authors:  J M Tanner; R D Gibbons
Journal:  J Pediatr Endocrinol       Date:  1994 Apr-Jun

9.  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

Review 10.  Clinical review: An automated method for determination of bone age.

Authors:  Hans Henrik Thodberg
Journal:  J Clin Endocrinol Metab       Date:  2009-04-28       Impact factor: 5.958

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  3 in total

1.  Assessing the Bone Age of Children in an Automatic Manner Newborn to 18 Years Range.

Authors:  Farzaneh Dehghani; Alireza Karimian; Mehri Sirous
Journal:  J Digit Imaging       Date:  2020-04       Impact factor: 4.056

2.  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

3.  An Automated System for Skeletal Maturity Assessment by Extreme Learning Machines.

Authors:  Marjan Mansourvar; Shahaboddin Shamshirband; Ram Gopal Raj; Roshan Gunalan; Iman Mazinani
Journal:  PLoS One       Date:  2015-09-24       Impact factor: 3.240

  3 in total

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