Publications by authors named "Atsuro Suzuki"

Article Synopsis
  • The study aimed to evaluate the quality of deep learning-reconstructed fluid-attenuated inversion recovery (DLR-FLAIR) images from undersampled data and compare them to fully sampled standard FLAIR images.
  • Thirty patients with white matter hyperintensities were examined, with fully sampled images taken and accelerated images created using one-third of that data through deep learning.
  • Results showed that DLR-FLAIR images had significantly less noise and better quality, as rated by neuroradiologists, and closely matched the visibility of hyperintensities found in standard FLAIR images, with 97% rated as nearly identical.
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To evaluate the quantitative accuracy of the measured speed of sound in ultrasound computed tomography for breast imaging, it is necessary to use a phantom with inclusions whose speed of sound is known. Accordingly, a phantom with known-speed-of-sound inclusions (e.g.

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Purpose: We developed a prototype CdTe SPECT system with 4-pixel matched collimator for brain study. This system provides high-energy-resolution (6.6%), high-sensitivity (220 cps/MBq/head), and high-spatial-resolution images.

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Background: A brain single-photon emission computed tomography (SPECT) system using cadmium telluride (CdTe) solid-state detectors was previously developed. This CdTe-SPECT system is suitable for simultaneous dual-radionuclide imaging due to its fine energy resolution (6.6 %).

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Objective: To improve the spatial resolution of brain single-photon emission computed tomography (SPECT), we propose a new brain SPECT system in which the detector heads are tilted towards the rotation axis so that they are closer to the brain. In addition, parallel detector heads are used to obtain the complete projection data set. We evaluated this parallel and tilted detector head system (PT-SPECT) in simulations.

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For high-sensitivity brain imaging, we have developed a two-head single-photon emission computed tomography (SPECT) system using a CdTe semiconductor detector and 4-pixel matched collimator (4-PMC). The term, '4-PMC' indicates that the collimator hole size is matched to a 2 × 2 array of detector pixels. By contrast, a 1-pixel matched collimator (1-PMC) is defined as a collimator whose hole size is matched to one detector pixel.

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We propose a wide aperture parallel-hole collimator that we call a 4-pixel matched collimator (4-PMC) for high-sensitivity SPECT imaging. The hole size of the 4-PMC is matched to four detector pixels; that is, there are four (2 × 2) pixels per collimator hole. By contrast, a 1-pixel matched collimator (1-PMC) is defined as a collimator whose hole size is matched to one detector pixel.

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The aim of the present study is to evaluate the validity of the simplified reference tissue model (SRTM) and of Logan graphical analysis with reference tissue (LGAR) for quantification of histamine H1 receptors (H1Rs) by using positron emission tomography (PET) with [11C]doxepin. These model-based analytic methods (SRTM and LGAR) are compared to Logan graphical analysis (LGA) and to the one-tissue model (1TM), using complete datasets obtained from 5 healthy volunteers. Since HIR concentration in the cerebellum can be regarded as negligibly small, the cerebellum was selected as the reference tissue in the present study.

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