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Epiphyses Localization for Bone Age Assessment Using the Discriminative Generalized Hough Transform

Part of the Informatik aktuell book series (INFORMAT)

Abstract

This paper presents the Discriminative Generalized Hough Transform (DGHT) as a robust and accurate method for the localization of epiphyseal regions in radiographs of the left hand. The technique utilizes a discriminative training approach to generate shape models with individual positive and negative model point weights for the Generalized Hough Transform. The framework incorporates a multi-level approach which reduces the searched region in two zooming steps, using specifically trained DGHT shape models. In addition to the standard method, a novel landmark combination approach is presented. Here, the N-best lists of individual landmark localizations are combined with anatomical constraints to achieve a globally optimal localization result for all 12 considered epiphyseal regions of interest. The technique has been applied to extract 12 epiphyseal regions of interest for a subsequent automatic bone age assessment. It achieved a localization success rate of 98.1% on a corpus with 412 left hand radiographs covering the age range from 3 to 19 years.

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Correspondence to Ferdinand Hahmann .

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Hahmann, F., Böer, G., Deserno, T., Schramm, H. (2014). Epiphyses Localization for Bone Age Assessment Using the Discriminative Generalized Hough Transform. In: Deserno, T., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2014. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54111-7_17

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