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Support Organization
National Research Foundation of Korea
Research Background
Revolutionary reduction in MRV data post-processing time, and application of hemodynamics-based diagnostic technology in clinical practice
Research Objectives
Development of an ultra-fast carotid blood flow analysis system based on MRV and machine learning
Research Methods
Collection of 3D velocity field MRV data inside the carotid artery from patients with carotid stenosis, and development of a carotid blood flow analysis system using machine learning
Main Results
Carotid blood flow analysis algorithm using machine learning and an optimized system through clinical testing
Blood Flow Analysis System
Using MRV and Machine Learning
Support Organization
Collaborative Research
Research Background
An MRI-based velocity/temperature/concentration measurement comparison results by groups around the world are needed to demonstrate the robust capabilities of the techniques.
Research Objectives
To visualize the velocity/temperature/concentration fields for the MRV challenge
Research Methods
Applying a combination of MRV, MRT and MRC to a building structures with complex 3D turbulent flow characteristics and comparing the results obtained by other groups
Main Results
The results are remarkably similar in nearly every way even with different types of MRI systems, different imaging protocols, and different reconstruction algorithms
MRV Challenge
Support Organization
National Research Foundation of Korea
Research Background
There is a need to develop a quantitative indicator that systematically integrates diverse but fragmented information, such as existing biological data, blood tests, and hemodynamics
Research Objectives
Development of a real-time precision medicine XR platform based on the Smart Hemodynamic Index integrating biological, physiological, and hemodynamic information
Research Methods
Development and integration of a hemodynamic simulation model and a vascular velocity field prediction model, establishment of a real-time prediction model using AI, and enhancement of medical data utilization models
Main Results
Smart Hemodynamic Index, Real-time 4D Velocity Field Measurement Technology, and Motion Recognition XR Glass
#ERC #Hemodynamic #AI
Center for Precision Medicine Platform Based on Smart Hemo-Dynamic Index
Support Organization
Collaborative Research
Research Background
Analysis of the impact on left atrial thrombus formation based on the results of Left Atrial Appendage Occlusion (LAAO) procedure
Research Objectives
Demonstrating the clinical significance of proper left atrial appendage occlusion in atrial fibrillation patients using 4D-Flow MRI
Research Methods
Creation of a left atrial phantom using CT imaging and 3D printing, collection of 4D velocity fields using 4D-Flow MRI, and analysis of the impact of left atrial appendage occlusion through hemodynamic analysis
Main Results
Confirmation that properly occluded left atrial appendage occlusion can minimize left atrial blood flow stasis and thrombogenesis to the greatest extent
#Hemodynamics #LAAO #MRV
Investigation of left atrial blood flow stasis and thrombogenesis in left atrial obstruction using 4D-Flow MRI
Support Organization
LG Electronics
Research Background
The main source of flow noise is Turbulent Kinetic Energy (TKE), and it is necessary to measure TKE in the refrigerator machinery room using MRV and design flow paths to minimize it
Research Objectives
Reduction of flow noise through improvement of the flow path shape in the machinery room
Research Methods
Creation of a flow shape in the machinery room that satisfies mechanical similarity through 3D printing, and measurement of average velocity and TKE in the machinery room using MRV
Main Results
Flow Path Model for Noise Reduction in the Refrigerator Machinery Room
Improvement of flow distribution and reduction of flow noise through flow visualization in the refrigerator machinery room
Support Organization
LG Electronics
Research Background
During compressor muffler design, it is necessary to consider the flow characteristics of the refrigerant in order to minimize pressure drop and ensure efficient heat exchange of the refrigerant
Research Objectives
Comparison of flow characteristics in the piston suction path of two reciprocating compressor muffler models
Research Methods
Creation of a compressor piston suction path shape that satisfies mechanical similarity through 3D printing, and measurement of average velocity and TKE inside the piston suction path using MRV
Main Results
Comparison of energy loss and pressure drop due to TKE
#TKE #MRV
Low-Noise Flow Path Design through Internal Flow Visualization and Comparison of Flow Characteristics in the Compressor Muffler Area
Blood Flow Analysis System
Using MRV and Machine Learning
Future
Mobility
Artificial
Intelligence
Energy &
Environment
Human
Healthcare
Background
Revolutionary reduction in MRV data post-processing time, and application of hemodynamics-based diagnostic technology in clinical practice
Objectives
Development of an ultra-fast carotid blood flow analysis system based on MRV and machine learning
Research Methods
Collection of 3D velocity field MRV data inside the carotid artery from patients with carotid stenosis, and development of a carotid blood flow analysis system using machine
This Research is supported by National Research Foundation of Korea (NRF)
#Hemodynamics #MRV #Machine learning
MRV Challenge 1, 2, and 3
Future
Mobility
Artificial
Intelligence
Energy &
Environment
Human
Healthcare
Background
To promote the broader application of MRV in engineering, the MRV Challenge was launched to demonstrate its capabilities and practices across research groups
Objectives
To evaluate consistency and improve experimental reliability by comparing measurement results obtained by different research groups
Research Methods
A combination of MRV, MRT, and MRC was applied to a flow phantom with complex 3D turbulent structures, and the results obtained by different research groups were compared
Collaborative Research
#Flow Visualization #MRV
Center for Precision Medicine Platform Based on Smart Hemo-Dynamic Index
Background
There is a need to develop a quantitative indicator that systematically integrates various fragmented data sources, including biological measurements, blood test results, and hemodynamic parameters.
Objectives
Development of a real-time precision medicine XR platform based on the Smart Hemodynamic Index integrating biological, physiological, and hemodynamic information
Research Methods
Development and integration of a hemodynamic simulation model and a vascular velocity field prediction model, establishment of a real-time prediction model using AI, and enhancement of medical data utilization models
This Research is supported by National Research Foundation of Korea (NRF)
#ERC #Hemodynamic #AI
