This study compares the performance and image quality of two gamma camera based PET systems of the first and latest generation. We investigated two dual head coincidence gamma cameras (PRISM 2000XP and AXIS, manufactured in 1997 and 2001 by Picker/Philips) predominantly in accordance with the NEMA NU2-1994 and NU2-2001 protocols. All performance parameters except for spatial resolution and image quality were determined after measuring a standard cylinder over several half-life periods. Scatter and random fractions were evaluated with the sinogram technique. In order to determine spatial resolution and image quality we used phantoms as described in the NEMA NU2-2001 protocol. The efficiency of the new system was found to be increased. True count rate at activity levels used in clinical conditions is improved and scatter fraction is decreased substantially. Accordingly, improved spatial resolution and image quality were observed with the new system. Altogether, the AXIS represents a further approach to the performance of dedicated positron emission tomographs.
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Jpn J Radiol
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Department of Biomedical Imaging, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia.
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January 2025
State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, PR China.
The elemental imaging of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) provides spatial information on elements and therefore can further investigate the growth or evolution processes of an analyte. However, the accurate determination of spatial information is limited by the decoupling between the elemental distribution and mass spectrometry signals. This phenomenon, which is more distinct when high-diffusion ablation cells are used, arises from the overlap of ablation and the transport dispersion of aerosols.
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Proton magnetic resonance spectroscopy (MRS) offers a non-invasive, repeatable, and reproducible method for in vivo metabolite profiling of the brain and other tissues. However, metabolite fingerprinting by MRS requires high signal-to-noise ratios for accurate metabolite quantification, which has traditionally been limited to large volumes of interest, compromising spatial fidelity. In this study, we introduce a new optimized pipeline that combines LASER MRS acquisition at 11.
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AIDA Lab. College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi Arabia.
The development of deep learning algorithms has transformed medical image analysis, especially in brain tumor recognition. This research introduces a robust automatic microbrain tumor identification method utilizing the VGG16 deep learning model. Microscopy magnetic resonance imaging (MMRI) scans extract detailed features, providing multi-modal insights.
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