Incorporation of correlated structural images in PET image reconstruction

Journal Article · Wed Nov 30 23:00:00 EST 1994 · IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States)

DOI:https://doi.org/10.1109/42.363105· OSTI ID:6873650

Ouyang, X ^[1]; Wong, W H; Chen, C T ^[2]; Johnson, V E ^[3]; Hu, X ^[4]

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1. Univ. of California, San Francisco, CA (United States). Dept. of Radiology
2. Univ. of Chicago, IL (United States)
3. Duke Univ., Durham, NC (United States). Inst. of Statistics and Decision Sciences
4. Univ. of Minnesota, Minneapolis, MN (United States). Dept. of Radiology

The authors report on a new method in which spatially correlated magnetic resonance (MR) or X-ray computed tomography (CT) images are employed as a source of prior information in the Bayesian reconstruction of positron emission tomography (PET) images. This new method incorporates the correlated structural images as anatomic templates which can be used for extracting information about boundaries that separate regions exhibiting different tissue characteristics. In order to avoid the possible introduction of artifacts caused by discrepancies between functional and anatomic boundaries, the authors propose a new method called the ''weighted line site'' method, in which a prior structural image is employed in a modified updating scheme for the boundary variable used in the iterative Bayesian reconstruction. This modified scheme is based on the joint probability of structural and functional boundaries. As to the structural information provided by CT or MR images, only those which have high joint probability with the corresponding PET data are used; whereas other boundary information that is not supported by the PET image is suppressed. The new method has been validated by computer simulation and phantom studies. The results of these validation studies indicate that this new method offers significant improvements in image quality when compared to other reconstruction algorithms, including the filtered backprojection (FBP) method and the maximum likelihood (ML) approach, as well as the Bayesian method without the use of the prior boundary information.

• DOE Contract Number: FG02-86ER60418
• OSTI ID: 6873650
• Journal Information: IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States), Journal Name: IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States) Vol. 13:4; ISSN 0278-0062; ISSN ITMID4
• Country of Publication: United States
• Language: English

Related Subjects

550601* -- Medicine-- Unsealed Radionuclides in Diagnostics
62 RADIOLOGY AND NUCLEAR MEDICINE
ACCURACY
COMPUTERIZED TOMOGRAPHY
CONTROL
DIAGNOSTIC TECHNIQUES
EMISSION COMPUTED TOMOGRAPHY
IMAGE PROCESSING
NMR IMAGING
OPTIMIZATION
POSITRON COMPUTED TOMOGRAPHY
PROCESSING
QUALITY CONTROL
TOMOGRAPHY