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Proceedings Paper

4D reconstruction of cardiac gated SPECT images using a content-adaptive deformable mesh model
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Paper Abstract

In this work, we present a four-dimensional reconstruction technique for cardiac gated SPECT images using a content-adaptive deformable mesh model. Cardiac gated SPECT images are affected by a high level of noise. Noise reduction methods usually do not account for cardiac motion and therefore introduce motion blur-an artifact that can decrease diagnostic accuracy. Additionally, image reconstruction methods typically rely on uniform sampling and Cartesian griding for image representation. The proposed method utilizes a mesh representation of the images in order to utilize the benefits of content-adaptive nonuniform sampling. The mesh model allows for accurate representation of important regions while significantly compressing the data. The content-adaptive deformable mesh model is generated by combining nodes generated on the full torso using pre-reconstructed emission and attenuation images with nodes accurately sampled on the left ventricle. Ventricular nodes are further displaced according to cardiac motion using our previously introduced motion estimation technique. The resulting mesh structure is then used to perform iterative image reconstruction using a mesh-based maximum-likelihood expectation-maximization algorithm. Finally, motion-compensated post-reconstruction temporal filtering is applied in the mesh domain using the deformable mesh model. Reconstructed images as well as quantitative evaluation show that the proposed method offers improved image quality while reducing the data size.

Paper Details

Date Published: 12 March 2010
PDF: 9 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76230E (12 March 2010); doi: 10.1117/12.844004
Show Author Affiliations
Thibault Marin, Illinois Institute of Technology (United States)
Miles N. Wernick, Illinois Institute of Technology (United States)
Yongyi Yang, Illinois Institute of Technology (United States)
Jovan G. Brankov, Illinois Institute of Technology (United States)

Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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