With a fixed time to acquire a magnetic resonance (MR) image, time can be spent to acquire better spatial resolution with decrease in signal-to-noise ratio (SNR) or decreased resolution with increase in SNR. This resolution/SNR tradeoff at fixed time has been investigated by a visual rater study using images of ex vivo mouse brains. Simulated images with a tradeoff between SNR and resolution were produced from high-quality, 3D isotropic mouse brain images to emulate shorter constant acquisition times. The tradeoff images spanned a range of SNRs (63-6) and isotropic resolutions (32-81 microm). Fourteen readers identified the image which best displayed neuroanatomy. Additional experiments tested for (i) intra-observer consistency, (ii) the effect of emulated scan time, and (iii) specifically biased questions pertaining to the perception of neuroanatomy. Optimal anatomical viewing depended primarily on the SNR of the images. Specifically, for fixed imaging time, preference lay in the SNR range of approximately 30-35 with strong consistency and there was minimal effect from overall imaging time.
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http://dx.doi.org/10.1002/nbm.1359 | DOI Listing |
Sensors (Basel)
January 2025
School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China.
Target detection is a core function of integrated sensing and communication (ISAC) systems. The traditional likelihood ratio test (LRT) target detection algorithm performs inadequately under low signal-to-noise ratio (SNR) conditions, and the performance of mainstream orthogonal frequency division multiplexing (OFDM) waveforms declines sharply in high-speed scenarios. To address these issues, an information-theory-based orthogonal time frequency space (OTFS)-ISAC target detection processing framework is proposed.
View Article and Find Full Text PDFCurr Oncol
January 2025
Department of Radiology, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective study was to improve image quality and accelerate imaging acquisition by using single-breath-hold T2-weighted HASTE with deep learning (DL) reconstruction (DL-HASTE) with a 3 mm slice thickness. MRI of the upper abdomen with DL-HASTE was performed in 35 participants (5 healthy volunteers and 30 patients) at 3 Tesla.
View Article and Find Full Text PDFClin Radiol
December 2024
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
Aim: To compare the image quality obtained using two accelerated high-resolution 3D fluid-attenuated inversion recovery (FLAIR) techniques for the brain-deep learning-reconstruction SPACE (DL-SPACE) and Wave-CAIPI FLAIR.
Materials And Methods: A total of 123 participants who underwent DL-SPACE and Wave-CAIPI FLAIR brain imaging were retrospectively reviewed. In a qualitative analysis, two radiologists rated the quality of each image, including the overall image quality, artifacts, sharpness, fine-structure conspicuity, and lesion conspicuity based on Likert scales.
Med Phys
January 2025
Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Background: Dedicated breast computed tomography (bCT) systems offer detailed imaging for breast cancer diagnosis and treatment. As new bCT generations are developed, it is important to evaluate their imaging performance and dose efficiency to understand differences over previous models.
Purpose: To characterize the imaging performance and dose efficiency of a second-generation (GEN2) bCT system and compare them to those of a first-generation (GEN1) system.
Front Neurosci
January 2025
Functional Magnetic Resonance Imaging (FMRI) Core, NIH, National Institute of Mental Health, Bethesda, MD, United States.
The use of submillimeter resolution functional magnetic resonance imaging (fMRI) is increasing in popularity due to the prospect of studying human brain activation non-invasively at the scale of cortical layers and columns. This method, known as laminar fMRI, is inherently signal-to-noise ratio (SNR)-limited, especially at lower field strengths, with the dominant noise source being of thermal origin. Furthermore, laminar fMRI is challenged with signal displacements due to draining vein effects in conventional gradient-echo blood oxygen level-dependent (BOLD) imaging contrasts.
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