Evaluation of reconstruction techniques for lung single photon emission tomography: A Monte Carlo study
2007 (English)In: Nuclear medicine communications, ISSN 0143-3636, Vol. 28, no 12, 929-936 p.Article in journal (Refereed) Published
BACKGROUND: In studies of the distribution of lung function, the image quality of lung single photon emission computed tomography (SPECT) is important and one factor influencing it is the reconstruction algorithm. AIM: To systematically evaluate ordered subsets expectation maximization (OSEM) and compare it with filtered back-projection (FBP) for lung SPECT with Tc. METHODS: The evaluation of the number of iterations used in OSEM was based on the image quality parameter contrast. The comparison between OSEM and FBP was based on trade-off plots between statistical noise and spatial resolution for different filter parameters, collimators and count-levels. A Monte Carlo technique was used to simulate SPECT studies of a digital thorax phantom containing two sets of activity: one with a homogeneous activity distribution within the lungs and the other with superposed high- and low-activity objects. Statistical noise in the reconstructed images was calculated as the coefficient of variation (CV) and spatial resolution as full width at half-maximum (FWHM). RESULTS: For the configuration studied, the OSEM reconstruction in combination with post-filtering should be used in lung SPECT studies with at least 60 MLEM equivalent iterations. Compared to FBP the spatial resolution was improved by about 1 mm. For a constant level of CV, a four-fold increase in count level resulted in an increased resolution of about 2 mm. Spatial resolution and cut-off frequency depends on what value of noise in the image is acceptable also increased by using a low-energy, high-resolution collimator for CV values above 3%. The choice of noise-reducing filter and cut-off frequency depends on what value of noise in the image is acceptable.
Place, publisher, year, edition, pages
United States: Lippincott Williams & Wilkins , 2007. Vol. 28, no 12, 929-936 p.
SPECT, Monte Carlo methods, image processing, lung
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-21152DOI: 10.1097/MNM.0b013e3282f1acacPubMedID: 18090220OAI: oai:DiVA.org:liu-21152DiVA: diva2:240758