ArticleInternational journal of computer assisted radiology and surgery2012
Web-based bone age assessment by content-based image retrieval for case-based reasoning.
Article in International journal of computer assisted radiology and surgery, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Assessing the Bone Age of Children in an Automatic Manner Newborn to 18 Years Range.Journal of digital imaging · 2020Article
- Article
- Automated bone age assessment: motivation, taxonomies, and challenges.Computational and mathematical methods in medicine · 2013Article
- Prototypes for content-based image retrieval in clinical practice.The open medical informatics journal · 2011Article
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4 authors.
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Abstract
purposeMaturity 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).
methodsA 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.
resultsLeave-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.
conclusionsCBIR 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.
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