2013
DOI: 10.1007/s11307-013-0683-2
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Scatter Characterization and Correction for Simultaneous Multiple Small-Animal PET Imaging

Abstract: The magnitude and spatial distribution of the scatter component in small-animal PET imaging of single and multiple subjects simultaneously were characterized, and its impact was evaluated in different situations. Scatter correction improves PET image quality and quantitative accuracy for single rat and simultaneous multiple mice and rat imaging studies, whereas its impact is insignificant in single mouse imaging.

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Cited by 13 publications
(8 citation statements)
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“…In this paper, unless stated otherwise, the images are reconstructed in 32 iterations (16 for the in vivo images) with 8 subsets per iteration, and an isotropic voxel resolution of 0.25 3 mm 3 . Although the reconstruction software is capable of attenuation-and scattercorrection, it was not used for the presented images (for accurate PET quantification, attenuation corrections should be employed [42]). Image fusion is achieved either manually or with AMIDE [43] and Imalytics [44].…”
Section: ) Reconstructionmentioning
confidence: 99%
“…In this paper, unless stated otherwise, the images are reconstructed in 32 iterations (16 for the in vivo images) with 8 subsets per iteration, and an isotropic voxel resolution of 0.25 3 mm 3 . Although the reconstruction software is capable of attenuation-and scattercorrection, it was not used for the presented images (for accurate PET quantification, attenuation corrections should be employed [42]). Image fusion is achieved either manually or with AMIDE [43] and Imalytics [44].…”
Section: ) Reconstructionmentioning
confidence: 99%
“…Iterative reconstruction algorithms can substantially improve both criteria because they include an appropriate statistical model to describe the data, resulting in better noise properties and thus improved precision, and they allow to accurately model image degrading effects such as attenuation, scatter and partial volume effects, resulting in a more accurate representation of the tracer distribution when a sufficient number of iterations are used [ 57 ]. Similar to the clinic, partial volume effects can be decreased by modelling the spatially variant detector response [ 54 , 57 ] and scatter can be estimated by using measurements in additional energy windows [ 58 ] or using the more complex single-scatter simulation technique [ 59 ]. Attenuation correction requires a co-registered map of attenuation coefficients at the relevant photon energy that for the majority of preclinical systems can be provided by CT [ 60 ].…”
Section: Case Presentationmentioning
confidence: 99%
“…These are commonly combined with simulation tools accounting for all physical aspects involved in the image acquisition process and characteristics of the imaging system to generate a simulated dataset that closely mimic clinical and experimental studies. The known features of computational models and simulated datasets provide precise information enabling to evaluate the impact of physical degrading factors inherent to the imaging process, [131][132][133][134][135] assess different design concepts and performance of medical imaging systems, [136][137][138][139][140][141][142][143][144][145][146][147][148][149][150] and advance the development and validation of new image segmentation, [151][152][153][154][155] registration, 156-161 reconstruction, [162][163][164][165][166][167] and processing techniques. [168][169][170][171][172][173][174][175] Likewise, the Digimouse and MOBY models served as optically heterogeneous virtual subjects for light propagation calculations to assess the impact of various parameters involved in optical molecular imaging techniques [176]…”
Section: C Medical Imaging Physicsmentioning
confidence: 99%
“…Two examples of studies carried out in the authors' lab (Geneva University Hospital) are briefly discussed below to illustrate the use of computational models in medical imaging physics research. Prasad and Zaidi 134 realistically modeled the LabPET™ small animal PET scanner using the 4-based Monte Carlo simulation platform to simulate particle transport within the animal model and the PET scanner, thus enabling to obtain simulated projection data of total events and to assess the magnitude, distribution, and origin of the scatter component in small animal PET. Figure 11 shows the setup for Monte Carlo simulation of single-and multiple-subject small animal PET imaging configurations.…”
Section: C Medical Imaging Physicsmentioning
confidence: 99%