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Deep Equilibrium Unfolding Learning for Noise Estimation and Removal in Optical Molecular Imaging.
Comput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
View Article and Find Full Text PDFFeasibility of very low iodine dose aortoiliac CT angiography using dual-source photon-counting detector CT.
Eur J Radiol
January 2025
Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA. Electronic address:
Purpose: To evaluate the feasibility of aortoiliac CT-Angiography (CTA) using dual-source photon-counting detector (PCD)-CT with minimal iodine dose.
Methods: This IRB-approved, single-center prospective study enrolled patients with indications for aortoiliac CTA from December 2022 to March 2023. All scans were performed using a first-generation dual-source PCD-CT.
Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising.
Invest Radiol
January 2025
From the Department of Radiology, Stanford University, Stanford, CA (K.W., M.J.M., A.M.L., A.B.S., A.J.H., D.B.E., R.L.B.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA (K.W.); GE HealthCare, Houston, TX (X.W.); GE HealthCare, Boston, MA (A.G.); and GE HealthCare, Menlo Park, CA (P.L.).
Objectives: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase inconsistency leads to quantitative errors and signal loss, limiting its utility. Multishot DWI (msDWI) offers reduced image distortion and blurring relative to single-shot methods but increases sensitivity to motion artifacts. Motion-compensated diffusion-encoding gradients (MCGs) reduce motion artifacts and could improve motion robustness of msDWI but come with the cost of extended echo time, further reducing signal.
View Article and Find Full Text PDFPreparation and photoelectric properties of Si:B nanowires with thermal evaporation method.
PLoS One
January 2025
College of Physics and Electronic Engineering, Hainan Normal University, HaiKou, China.
We have successfully prepared a significant number of nanowires from non-toxic silicon sources. Compared to the SiO silicon source used in most other articles, our preparation method is much safer. It provides a simple and harmless new preparation method for the preparation of silicon nanowires.
View Article and Find Full Text PDFConvolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation.
PLoS One
January 2025
Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran.
CNN is considered an efficient tool in brain image segmentation. However, neonatal brain images require specific methods due to their nature and structural differences from adult brain images. Hence, it is necessary to determine the optimal structure and parameters for these models to achieve the desired results.
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