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Title: Bayesian SPECT lung imaging for visualization and quantification of pulmonary perfusion

Journal Article · · IEEE Transactions on Nuclear Science
DOI:https://doi.org/10.1109/23.737662· OSTI ID:323711

In this paper, the authors quantitatively and qualitatively examine the use of a Gibbs prior in maximum a posteriori (MAP) reconstruction of SPECT images of pulmonary perfusion using the expectation-maximization (EM) algorithm. This Bayesian approach is applied to SPECT projection data acquired from a realistic torso phantom with spherical defects in the lungs simulating perfusion deficits. Both the scatter subtraction constant (k) and the smoothing parameter beta ({beta}) characterizing the prior are varied to study their effect on image quality and quantification. Region of interest (ROI) analysis is used to compare MAP-EM radionuclide concentration estimates with those derived from a ``clinical`` implementation of filtered backprojection (CFBP), and a quantitative implementation of FBP (QFBP) utilizing nonuniform attenuation and scatter compensation. Qualitatively, the MAP-EM images contain reduced artifacts near the lung boundaries relative to the FBP implementations. Generally, the MAP-EM image`s visual quality and the ability to discern the areas of reduced radionuclide concentration in the lungs depend on the value of {beta} and the total number of iterations. For certain choices of {beta} and total iterations, MAP-EM lung images are visually comparable to FBP. Based on profile and ROI analysis, SPECT QFBP and MAP-EM images have the potential to provide quantitatively accurate reconstructions when compared to CFBP. The computational burden, however, is greater for the MAP-EM approach. To demonstrate the clinical efficacy of the methods, the authors present pulmonary images of a patient with lung cancer.

Sponsoring Organization:
National Cancer Inst., Bethesda, MD (United States); USDOE, Washington, DC (United States)
DOE Contract Number:
FG02-96ER62150
OSTI ID:
323711
Report Number(s):
CONF-971147-; ISSN 0018-9499; TRN: 99:004337
Journal Information:
IEEE Transactions on Nuclear Science, Vol. 45, Issue 6Pt2; Conference: Institute of Electrical and Electronic Engineers (IEEE) nuclear science symposium and medical imaging conference, Albuquerque, NM (United States), 11-13 Nov 1997; Other Information: PBD: Dec 1998
Country of Publication:
United States
Language:
English