AIMC Topic: Magnetic Resonance Imaging
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Deep learning-based velocity antialiasing of 4D-flow MRI.
Magnetic resonance in medicine
Apr 5, 2022
PURPOSE: To develop a convolutional neural network (CNN) for the robust and fast correction of velocity aliasing in 4D-flow MRI.
CardiSort: a convolutional neural network for cross vendor automated sorting of cardiac MR images.
European radiology
Apr 4, 2022
OBJECTIVES: To develop an image-based automatic deep learning method to classify cardiac MR images by sequence type and imaging plane for improved clinical post-processing efficiency.
The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects.
Human brain mapping
Apr 4, 2022
Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus,...
Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI.
Korean journal of radiology
Apr 4, 2022
OBJECTIVE: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging...
High fidelity deep learning-based MRI reconstruction with instance-wise discriminative feature matching loss.
Magnetic resonance in medicine
Apr 3, 2022
PURPOSE: To improve reconstruction fidelity of fine structures and textures in deep learning- (DL) based reconstructions.
Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram.
European radiology
Apr 2, 2022
OBJECTIVES: To implement a pipeline to automatically segment the ROI and to use a nomogram integrating the MRI-based radiomics score and clinical variables to predict responses to neoadjuvant chemotherapy (NAC) in osteosarcoma patients.
Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy.
Epilepsia
Apr 1, 2022
OBJECTIVE: Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning usin...
Detection of Differences in Longitudinal Cartilage Thickness Loss Using a Deep-Learning Automated Segmentation Algorithm: Data From the Foundation for the National Institutes of Health Biomarkers Study of the Osteoarthritis Initiative.
Arthritis care & research
Apr 1, 2022
OBJECTIVE: To study the longitudinal performance of fully automated cartilage segmentation in knees with radiographic osteoarthritis (OA), we evaluated the sensitivity to change in progressor knees from the Foundation for the National Institutes of H...
Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.
NMR in biomedicine
Mar 31, 2022
Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical...
Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI.
Computer methods and programs in biomedicine
Mar 31, 2022
PURPOSE: We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using Pre- and Post-treatment MR images based on deep learning (DL).
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