AIMC Topic: Magnetic Resonance Imaging
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The Curative Effect of Pregabalin in the Treatment of Postherpetic Neuralgia Analyzed by Deep Learning-Based Brain Resting-State Functional Magnetic Resonance Images.
Contrast media & molecular imaging
May 10, 2022
This work aimed to investigate the brain resting-state functional magnetic resonance imaging (fMRI) technology based on the depth autoencoders algorithm and to evaluate the clinically curative effect of pregabalin in the treatment of postherpetic neu...
Deep learning kidney segmentation with very limited training data using a cascaded convolution neural network.
PloS one
May 9, 2022
BACKGROUND: Deep learning segmentation requires large datasets with ground truth. Image annotation is time consuming and leads to shortages of ground truth data for clinical imaging. This study is to investigate the feasibility of kidney segmentation...
Automatic segmentation model of intercondylar fossa based on deep learning: a novel and effective assessment method for the notch volume.
BMC musculoskeletal disorders
May 6, 2022
BACKGROUND: Notch volume is associated with anterior cruciate ligament (ACL) injury. Manual tracking of intercondylar notch on MR images is time-consuming and laborious. Deep learning has become a powerful tool for processing medical images. This stu...
Editorial for "Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning".
Journal of magnetic resonance imaging : JMRI
May 5, 2022
A Novel Framework With Weighted Decision Map Based on Convolutional Neural Network for Cardiac MR Segmentation.
IEEE journal of biomedical and health informatics
May 5, 2022
For diagnosing cardiovascular disease, an accurate segmentation method is needed. There are several unresolved issues in the complex field of cardiac magnetic resonance imaging, some of which have been partially addressed by using deep neural network...
AutoAtlas: Neural Network for 3D Unsupervised Partitioning and Representation Learning.
IEEE journal of biomedical and health informatics
May 5, 2022
We present a novel neural network architecture called AutoAtlas for fully unsupervised partitioning and representation learning of 3D brain Magnetic Resonance Imaging (MRI) volumes. AutoAtlas consists of two neural network components: one neural netw...
Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning.
Journal of magnetic resonance imaging : JMRI
May 4, 2022
BACKGROUND: Segmenting the whole heart over the cardiac cycle in 4D flow MRI is a challenging and time-consuming process, as there is considerable motion and limited contrast between blood and tissue.
Malignant Bone Tumors Diagnosis Using Magnetic Resonance Imaging Based on Deep Learning Algorithms.
Medicina (Kaunas, Lithuania)
May 4, 2022
: Malignant bone tumors represent a major problem due to their aggressiveness and low survival rate. One of the determining factors for improving vital and functional prognosis is the shortening of the time between the onset of symptoms and the momen...
Auxiliary Diagnosis of Lung Cancer with Magnetic Resonance Imaging Data under Deep Learning.
Computational and mathematical methods in medicine
May 4, 2022
This study was aimed at two image segmentation methods of three-dimensional (3D) U-shaped network (U-Net) and multilevel boundary sensing residual U-shaped network (RUNet) and their application values on the auxiliary diagnosis of lung cancer. In thi...
Brain network connectivity feature extraction using deep learning for Alzheimer's disease classification.
Neuroscience letters
May 2, 2022
Early diagnosis and therapeutic intervention for Alzheimer's disease (AD) is currently the only viable option for improving clinical outcomes. Combining structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imag...
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