Registration-based segmentation with articulated model from multipostural magnetic resonance images for hand bone motion animation

Medical Physics
Hsin-Chen ChenYung-Nien Sun

Abstract

The quantitative measurements of hand bones, including volume, surface, orientation, and position are essential in investigating hand kinematics. Moreover, within the measurement stage, bone segmentation is the most important step due to its certain influences on measuring accuracy. Since hand bones are small and tubular in shape, magnetic resonance (MR) imaging is prone to artifacts such as nonuniform intensity and fuzzy boundaries. Thus, greater detail is required for improving segmentation accuracy. The authors then propose using a novel registration-based method on an articulated hand model to segment hand bones from multipostural MR images. The proposed method consists of the model construction and registration-based segmentation stages. Given a reference postural image, the first stage requires construction of a drivable reference model characterized by hand bone shapes, intensity patterns, and articulated joint mechanism. By applying the reference model to the second stage, the authors initially design a model-based registration pursuant to intensity distribution similarity, MR bone intensity properties, and constraints of model geometry to align the reference model to target bone regions of the given postural image. The...Continue Reading

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Citations

Aug 22, 2013·IEEE Transactions on Bio-medical Engineering· Hsin-Chen Chen Yung-Nien Sun
Oct 5, 2013·Measurement Science & Technology·Hsin-Chen ChenKai-Nan An

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