Scan-specific deep learning strategies have been proposed for parallel imaging reconstruction in which auto-calibrated signals (ACS) are used for training. Here, we introduce methods to objectively optimize architecture and training details. In addit...
IEEE transactions on bio-medical engineering
Aug 1, 2025
The prolonged scan time of chemical exchange saturation transfer (CEST) imaging, caused by multiple data acquisitions over the varying saturation offset frequencies, necessitates accelerated imaging techniques. In this work, the artifact information ...
B-line artifacts in lung ultrasound, pivotal for diagnosing pulmonary conditions, warrant automated recognition to enhance diagnostic accuracy. In this paper, a lung ultrasound B-line vertical artifact identification method based on radio frequency (...
Radiographics : a review publication of the Radiological Society of North America, Inc
Jul 1, 2025
Coronary CT angiography (CCTA) has been widely used as a noninvasive modality for accurate assessment of coronary artery disease (CAD) in clinical settings. However, the following limitations of CCTA remain issues of interest: motion, stair-step, and...
Functional magnetic resonance imaging (fMRI) has opened new frontiers in neuroscience by instrumentally driving our understanding of brain function and development. Despite its substantial successes, fMRI studies persistently encounter obstacles stem...
Journal of magnetic resonance (San Diego, Calif. : 1997)
Jul 1, 2025
Undersampling accelerates signal acquisition at the expense of introducing artifacts. Removing these artifacts is a fundamental problem in signal processing and this task is also called signal reconstruction. Through modeling signals as the superimpo...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 1, 2025
High-quality computed tomography (CT) scans are essential for accurate diagnostic and therapeutic decisions, but the presence of metal objects within the body can produce distortions that lower image quality. Deep learning (DL) approaches using image...
PURPOSE: To assess the image quality and biventricular function utilizing a free-breathing artificial intelligence cine method with motion correction (FB AI MOCO).
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Banding artifacts in images stem from limitations in color bit depth, image compression, or over-editing, significantly degrades image quality, especially in regions with smooth gradients. Image debanding is about eliminating these artifacts while pr...
PURPOSE: To develop and evaluate a physics-driven, saturation contrast-aware, deep-learning-based framework for motion artifact correction in CEST MRI.
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