osem-psf + tof reconstruction algorithm (Siemens AG)
90
Structured Review
Siemens AG
osem-psf + tof reconstruction algorithm
Osem Psf + Tof Reconstruction Algorithm, supplied by Siemens AG, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tof+osem+algorithm/osem/pm38289518-73-6-5
Average 90 stars, based on 1 article reviews
Osem Psf + Tof Reconstruction Algorithm, supplied by Siemens AG, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tof+osem+algorithm/osem/pm38289518-73-6-5
Average 90 stars, based on 1 article reviews
osem-psf + tof reconstruction algorithm - by Bioz Stars,
2026-10
90/100 stars
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other:Article Title: ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages Article Snippet: Images were reconstructed using the Article Title: Reduction of SPECT acquisition time using deep learning: A phantom study. Article Snippet: Single photon emission computed tomography (SPECT) procedures are characterized by long acquisition time to acquire diagnostically acceptable image data.. The goal of this investigation was to assess the feasibility of using a deep convolutional neural network (DCNN) to reduce the acquisition time.. The DCNN was implemented using the PyTorch and trained using image data from standard SPECT quality phantoms. Article Title: Optimization of BMI-Based Images for Overweight and Obese Patients - Implications on Image Quality, Quantification, and Radiation Dose in Whole Body 18 F-FDG PET/CT Imaging. Article Snippet: Purpose In PET/CT imaging, the activity of the 18F-FDG activity is injected either based on patient body weight (BW) or body mass index (BMI).. The purpose of this study was to optimise BMI-based whole body 18F-FDG PET images obtained from overweight and obese patients and assess their image quality, quantitative value and radiation dose in comparison to BW-based images.. Methods The NEMA-IEC-body phantom was scanned using the mCT 128-slice scanner. Article Title: ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages. Article Snippet: Images were reconstructed using the Positron Emission Tomography:Article Title: Image reconstruction Article Snippet: .. Specific implementations of these approaches, in use by industry for clinical PET imaging, include: Article Title: Likelihood-Scheduled Score-Based Generative Modeling for Fully 3D PET Image Reconstruction Article Snippet: Medical image reconstruction with pretrained score-based generative models (SGMs) has advantages over other existing state-of-the-art deeplearned reconstruction methods, including improved resilience to different scanner setups and advanced image distribution modeling.. SGM-based reconstruction has recently been applied to simulated positron emission tomography (PET) datasets, showing improved contrast recovery for out-of-distribution lesions relative to the state-of-the-art.. However, existing methods for SGMbased reconstruction from PET data suffer from slow reconstruction, burdensome hyperparameter tuning and slice inconsistency effects (in 3D). Imaging:Article Title: Image reconstruction Article Snippet: .. Specific implementations of these approaches, in use by industry for clinical PET imaging, include: |
