HANDX: a model-based system for automatic segmentation of bones from digital hand radiographs

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Abstract
The authors detail the design and implementation of HANDX, a model-based computer vision system used in the domain of medical image processing. Given a digitized hand radiograph, HANDX segments out specific bones and measures particular parameters of the bones, without requiring specific characterization of noise variations in background contrast and anatomical differences which arise from patient variation. Observer variability is reduced by the system, and the resulting measurement may be useful for detecting short-term skeletal growth abnormalities in children and may additional clinical applications. The overall system is modularized into three stages: preprocessing, segmentation, and measurement. In the preprocessing state model-based histogram modification is used to normalize the radiograph. The histogram model is based on the physics of the imaging process. The segmentation stage finds and outlines specific bones using domain-dependent and domain-independent knowledge of hand anatomy and physiology and image edges. The measurement stage obtains clinically useful quantitative parameters from the segmented image.

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