The aim of this work is to develop an automated system for skeletal bone age evaluation. Skeletal bone age assessment is a common and time-consuming task in pediatric radiology. We describe a system that implements the EMROI (Epiphyseal/Metaphyseal Region Of Interest) extraction method by image processing techniques. Each EMROI is localized on the image, by using an analysis of its gray levels. Then the bones in the EMROI are extracted by using the DoG (Difference of Gaussians) filter and enhanced using a novel adaptive thresholding obtained by histogram processing. Finally, the main features of these bones are extracted for the stage TW2 (Tanner Whitehouse) evaluation. Results obtained on a sample of 20 X-rays are discussed. With respect to the other existing automated approaches to compute the bone age, the proposed method requires less user feedback on system's settings and is very versatile since it doesn't depend strongly on features of the X-ray acquisition.

Epiphysis and metaphysis extraction and classification by adaptive thresholding and DoG filtering for automated skeletal bone age analysis

GIORDANO, Daniela;LEONARDI, Rosalia Maria;SPAMPINATO, CONCETTO
2007-01-01

Abstract

The aim of this work is to develop an automated system for skeletal bone age evaluation. Skeletal bone age assessment is a common and time-consuming task in pediatric radiology. We describe a system that implements the EMROI (Epiphyseal/Metaphyseal Region Of Interest) extraction method by image processing techniques. Each EMROI is localized on the image, by using an analysis of its gray levels. Then the bones in the EMROI are extracted by using the DoG (Difference of Gaussians) filter and enhanced using a novel adaptive thresholding obtained by histogram processing. Finally, the main features of these bones are extracted for the stage TW2 (Tanner Whitehouse) evaluation. Results obtained on a sample of 20 X-rays are discussed. With respect to the other existing automated approaches to compute the bone age, the proposed method requires less user feedback on system's settings and is very versatile since it doesn't depend strongly on features of the X-ray acquisition.
2007
9781424407880
Feature extraction; Image analysis; Histogram processing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/75950
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