Essays about: "4D flow MRI"
Showing result 1 - 5 of 15 essays containing the words 4D flow MRI.
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1. Reconstruction of Accelerated Cardiovascular MRI data
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : Magnetic resonance imaging (MRI), is a noninvasive medical imaging testing techniquewhich is used to produce detailed images of internal structure of the human body, includingbones, muscles, organs, and blood vessels. MRI scanners use large magnets and radiowaves to create images of the body. READ MORE
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2. Generalized super-resolution of 4D Flow MRI : extending capabilities using ensemble learning
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : 4D Flow Magnet Resonance Imaging (4D Flow MRI) is a novel non-invasive technique for imaging of cardiovascular blood flow. However, when utilized as a stand-alone analysis method, 4D Flow MRI has certain limitations including limited spatial resolution and noise artefacts, motivating the application of dedicated post-processing tools. READ MORE
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3. Deep learning for temporal super-resolution of 4D Flow MRI
University essay from KTH/Matematik (Avd.)Abstract : The accurate assessment of hemodynamics and its parameters play an important role when diagnosing cardiovascular diseases. In this context, 4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique that facilitates hemodynamic parameter assessment as well as quantitative and qualitative analysis of three-directional flow over time. READ MORE
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4. Optimization-Based Geometry Correction Of Blood Flow CFD Simulations Using 4D-Flow Data
University essay from Lunds universitet/Institutionen för energivetenskaperAbstract : 4D-flow is a powerful tool capable of capturing 3-dimensional, time-resolved flow measurements of blood flow in the body. Their current use is limited by resolution and scan times. A proposed solution is to use Simulation Based Imaging (SBI). READ MORE
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5. Using Deep Learning to SegmentCardiovascular 4D Flow MRI : 3D U-Net for cardiovascular 4D flow MRI segmentation and Bayesian 3D U-Net for uncertainty estimation
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Deep convolutional neural networks (CNN’s) have achieved state-of-the-art accuraciesfor multi-class segmentation in biomedical image science. In this thesis, A 3D U-Net isused to segment 4D flow Magnetic Resonance Images that include the heart and its largevessels. READ MORE