AIMC Topic: Magnetic Resonance Imaging
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Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning.
Magnetic resonance in medicine
Jun 1, 2022
PURPOSE: To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data.
Scan-Specific Generative Neural Network for MRI Super-Resolution Reconstruction.
IEEE transactions on medical imaging
Jun 1, 2022
The interpretation and analysis of Magnetic resonance imaging (MRI) benefit from high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is time-consuming and costly, which increases the potential for motion artifact...
Clinical Variables, Deep Learning and Radiomics Features Help Predict the Prognosis of Adult Anti-N-methyl-D-aspartate Receptor Encephalitis Early: A Two-Center Study in Southwest China.
Frontiers in immunology
Jun 1, 2022
OBJECTIVE: To develop a fusion model combining clinical variables, deep learning (DL), and radiomics features to predict the functional outcomes early in patients with adult anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis in Southwest China.
Deep learning architectures for Parkinson's disease detection by using multi-modal features.
Computers in biology and medicine
May 28, 2022
BACKGROUND: The use of multi-modal features for improving the diagnosing accuracy of Parkinson's disease (PD) is still under consideration.
Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Marrow Characterization From Whole-Body MRI: A Multicentric Feasibility Study.
Investigative radiology
May 27, 2022
OBJECTIVES: Disseminated bone marrow (BM) involvement is frequent in multiple myeloma (MM). Whole-body magnetic resonance imaging (wb-MRI) enables to evaluate the whole BM. Reading of such whole-body scans is time-consuming, and yet radiologists can ...
Towards autonomous analysis of chemical exchange saturation transfer experiments using deep neural networks.
Journal of biomolecular NMR
May 27, 2022
Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structur...
Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time.
European radiology
May 26, 2022
OBJECTIVES: To investigate the feasibility of automatically identifying normal scans in ultrafast breast MRI with artificial intelligence (AI) to increase efficiency and reduce workload.
Deep learning-based automated segmentation of eight brain anatomical regions using head CT images in PET/CT.
BMC medical imaging
May 26, 2022
OBJECTIVE: We aim to propose a deep learning-based method of automated segmentation of eight brain anatomical regions in head computed tomography (CT) images obtained during positron emission tomography/computed tomography (PET/CT) scans. The brain r...
Magnetic Resonance Imaging Features on Deep Learning Algorithm for the Diagnosis of Nasopharyngeal Carcinoma.
Contrast media & molecular imaging
May 25, 2022
The objective of this research was to investigate the application values of magnetic resonance imaging (MRI) features of the deep learning-based image super-resolution reconstruction algorithm optimized convolutional neural network (OPCNN) algorithm ...
Znet: Deep Learning Approach for 2D MRI Brain Tumor Segmentation.
IEEE journal of translational engineering in health and medicine
May 23, 2022
BACKGROUND: Detection and segmentation of brain tumors using MR images are challenging and valuable tasks in the medical field. Early diagnosing and localizing of brain tumors can save lives and provide timely options for physicians to select efficie...
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