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Showing 731 to 740 of 1686 articles

A Novel Deep Learning Approach for Tracking Regions of Interest in Ultrasound Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Due to their great success in learning a universal object similarity metric, Siamese Trackers have been adopted for motion tracking a Region of Interest (ROI) in Ultrasound (US) image sequences. However, these Fully Convolutional Siamese networks (Si...
Motion Deep Learning Ultrasonography Carotid Arteries Algorithms
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Retrospective Detection and Suppression of Dark-Rim Artifacts in First-Pass Perfusion Cardiac MRI Enabled by Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
The dark-rim artifact (DRA) remains an important challenge in the routine clinical use of first-pass perfusion (FPP) cardiac magnetic resonance imaging (cMRI). The DRA mimics the appearance of perfusion defects in the subendocardial wall and reduces ...
Deep Learning Magnetic Resonance Imaging Retrospective Studies Artifacts Myocardial Perfusion Imaging Humans Image Interpretation, Computer-Assisted Perfusion
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Deep Learning-Based Segmentation and Uncertainty Assessment for Automated Analysis of Myocardial Perfusion MRI Datasets Using Patch-Level Training and Advanced Data Augmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
In this work, we develop a patch-level training approach and a task-driven intensity-based augmentation method for deep-learning-based segmentation of motion-corrected perfusion cardiac magnetic resonance imaging (MRI) datasets. Further, the proposed...
Perfusion Uncertainty Magnetic Resonance Imaging Heart Deep Learning
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End to End Unsupervised Rigid Medical Image Registration by Using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
In this paper, we focus on the issue of rigid medical image registration using deep learning. Under ultrasound, the moving of some organs, e.g., liver and kidney, can be modeled as rigid motion. Therefore, when the ultrasound probe keeps stationary, ...
Neural Networks, Computer Liver Ultrasonography
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A Patch-Wise Deep Learning Approach for Myocardial Blood Flow Quantification with Robustness to Noise and Nonrigid Motion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Quantitative analysis of dynamic contrast-enhanced cardiovascular MRI (cMRI) datasets enables the assessment of myocardial blood flow (MBF) for objective evaluation of ischemic heart disease in patients with suspected coronary artery disease. State-o...
Coronary Circulation Deep Learning Reproducibility of Results Coronary Artery Disease Magnetic Resonance Imaging Humans
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Deep Phenotypic Cell Classification using Capsule Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Recent developments in ultra-high-throughput microscopy have created a new generation of cell classification methodologies focused solely on image-based cell phenotypes. These image-based analyses enable morphological profiling and screening of thous...
Microscopy Neural Networks, Computer Image Processing, Computer-Assisted
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Placental Super Micro-vessels Segmentation Based on ResNeXt with Convolutional Block Attention and U-Net.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Accurate placenta super micro-vessels segmentation is the key to diagnose placental diseases. However, the current automatic segmentation algorithm has issues of information redundancy and low information utilization, which reduces the segmentation a...
Pregnancy Female Algorithms Attention Placenta Image Processing, Computer-Assisted Neural Networks, Computer Humans
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Ultrasound Image Quality Evaluation using a Structural Similarity Based Autoencoder.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Ultrasound (US) imaging is a widely used clinical technique that requires extensive training to use correctly. Good quality US images are essential for effective interpretation of the results, however numerous sources of error can impair quality. Cur...
Humans Ultrasonography Machine Learning Artifacts
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Deep learning in resting-state fMRI.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Modeling the rich, dynamic spatiotemporal variations captured by human brain functional magnetic resonance imaging (fMRI) data is a complicated task. Analysis at the brain's regional and connection levels provides more straightforward biological inte...
Brain Mapping Magnetic Resonance Imaging Machine Learning Humans Deep Learning Brain
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Automatic Deep Learning Segmentation and Quantification of Epicardial Adipose Tissue in Non-Contrast Cardiac CT scans.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
An Automatic deep learning semantic segmentation (ADLS) using DeepLab-v3-plus technique is proposed for a full and accurate whole heart Epicardial adipose tissue (EAT) segmentation from non-contrast cardiac CT scan. The ADLS algorithm was trained on ...
Tomography, X-Ray Computed Thorax Pericardium Adipose Tissue Deep Learning
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