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Chun, Se Young
Bio-Medical Image Processing Lab (BMIPL)
Research Interests
  • Inverse problem, sparse signal, multimodal information, diffeomorphic alignment, statistical learning, medical imaging

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Spatial Resolution Properties of Motion-Compensated Tomographic Image Reconstruction Methods

Cited 7 times inthomson ciCited 8 times inthomson ci
Title
Spatial Resolution Properties of Motion-Compensated Tomographic Image Reconstruction Methods
Author
Chun, Se YoungFessler, Jeffrey A.
Issue Date
2012-07
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE TRANSACTIONS ON MEDICAL IMAGING, v.31, no.7, pp.1413 - 1425
Abstract
Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.
URI
https://scholarworks.unist.ac.kr/handle/201301/7985
URL
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84863424615
DOI
10.1109/TMI.2012.2192133
ISSN
0278-0062
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