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Proceedings Paper

Incorporation of noise and prior images in penalized-likelihood reconstruction of sparse data
Author(s): Yifu Ding; Jeffrey H. Siewerdsen; J. Webster Stayman
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Paper Abstract

Many imaging scenarios involve a sequence of tomographic data acquisitions to monitor change over time - e.g., longitudinal studies of disease progression (tumor surveillance) and intraoperative imaging of tissue changes during intervention. Radiation dose imparted for these repeat acquisitions present a concern. Because such image sequences share a great deal of information between acquisitions, using prior image information from baseline scans in the reconstruction of subsequent scans can relax data fidelity requirements of follow-up acquisitions. For example, sparse data acquisitions, including angular undersampling and limited-angle tomography, limit exposure by reducing the number of acquired projections. Various approaches such as prior-image constrained compressed sensing (PICCS) have successfully incorporated prior images in the reconstruction of such sparse data. Another technique to limit radiation dose is to reduce the x-ray fluence per projection. However, many methods for reconstruction of sparse data do not include a noise model accounting for stochastic fluctuations in such low-dose measurements and cannot balance the differing information content of various measurements. In this paper, we present a prior-image, penalized-likelihood estimator (PI-PLE) that utilizes prior image information, compressed-sensing penalties, and a Poisson noise model for measurements. The approach is applied to a lung nodule surveillance scenario with sparse data acquired at low exposures to illustrate performance under cases of extremely limited data fidelity. The results show that PI-PLE is able to greatly reduce streak artifacts that otherwise arise from photon starvation, and maintain high-resolution anatomical features, whereas traditional approaches are subject to streak artifacts or lower-resolution images.

Paper Details

Date Published: 3 March 2012
PDF: 7 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 831324 (3 March 2012); doi: 10.1117/12.911667
Show Author Affiliations
Yifu Ding, The Johns Hopkins Univ. (United States)
Jeffrey H. Siewerdsen, The Johns Hopkins Univ. (United States)
J. Webster Stayman, The Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 8313:
Medical Imaging 2012: Physics of Medical Imaging
Norbert J. Pelc; Robert M. Nishikawa; Bruce R. Whiting, Editor(s)

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