2010
DOI: 10.1118/1.3315368
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Attenuation‐emission alignment in cardiac PET/CT based on consistency conditions

Abstract: Purpose:In cardiac PET and PET/CT imaging, misaligned transmission and emission images are a common problem due to respiratory and cardiac motion. This misalignment leads to erroneous attenuation correction and can cause errors in perfusion mapping and quantification. This study develops and tests a method for automated alignment of attenuation and emission data. Methods: The CT-based attenuation map is iteratively transformed until the attenuation corrected emission data minimize an objective function based o… Show more

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Cited by 43 publications
(36 citation statements)
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“…These 2-D studies were followed by research on 3-D templates, this time using simplex methods evaluated in simulations and phantoms 189 and, later, in cardiac PET/CT patients using rigidbody registration. 190 More recent proposals involve TOF PET data and iterative methods. Maximum likelihood reconstruction of the transformation between PET and CT images and activity (MLTA), estimating parameters of a rigid-body transformation, was subject of a 2-D simulation study.…”
Section: C3 Registration Of Available µ-Mapsmentioning
confidence: 99%
“…These 2-D studies were followed by research on 3-D templates, this time using simplex methods evaluated in simulations and phantoms 189 and, later, in cardiac PET/CT patients using rigidbody registration. 190 More recent proposals involve TOF PET data and iterative methods. Maximum likelihood reconstruction of the transformation between PET and CT images and activity (MLTA), estimating parameters of a rigid-body transformation, was subject of a 2-D simulation study.…”
Section: C3 Registration Of Available µ-Mapsmentioning
confidence: 99%
“…The field has developed since then, but the main factors that affect the quantification using SPECT remain the same. Many factors influence the accuracy of the quantification of PET/CT images and include: correction for attenuation, noise, image resolution, and ROI (region of interest) definitions (Alessio et al, 2010;Boellard et al, 2004;Kinahan et al, 1998). Regarding all quantifications, it can be very useful to perform phantom measurements mimicking the patient situation as good as possible.…”
Section: Radiation Dosimetry In the Clinical Situationmentioning
confidence: 99%
“…Sinogram before correction contains some information that can aid the µmap creation and Helgason-Ludwig Consistency Conditions (HLCC)was formulated to extract the information [11]. However, HLCC alone is not sufficient and sometimes not valid due to sparse data sampling.…”
Section: Introductionmentioning
confidence: 99%