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Newly Proposed Method With Noise-Reduction and Smoothing for Computational Fluid Dynamics Using Low-Resolution
Yoshiki Yanagita1, H N Abhilash2, S M Abdul Khader2
1Graduate School of Life Science System and Engineering, Kyushu Institute of Technology, Fukuoka, Japan.
Summary
Researchers developed a new method to reduce surface roughness in medical images, improving computational fluid dynamics (CFD) accuracy for wall shear stress (WSS) calculations in arteries while minimizing volume changes.
Area of Science:
- Biomedical Engineering
- Medical Imaging Analysis
- Computational Fluid Dynamics
Background:
- Wall shear stress (WSS) from medical images and CFD aids medical support.
- Low-resolution medical images introduce noise, increasing surface roughness and reducing WSS calculation accuracy.
- Standard smoothing methods for geometries can cause undesirable volume changes.
Purpose of the Study:
- To develop a method for reducing surface roughness in low-resolution medical images with minimal volume changes.
- To improve the accuracy of WSS calculations in carotid and cerebral arteries using CFD.
- To enhance medical support based on readily available medical imaging data.
Main Methods:
- Developed a novel approach combining coordinate point interpolation with selective low-frequency noise removal.
- Applied the method to 12 carotid artery and 1 cerebral artery geometries from medical checkup images.
- Compared surface roughness, volume changes, and CFD-derived WSS before and after applying the smoothing technique.
Main Results:
- Reduced surface roughness in carotid artery geometries by approximately 27%-32%.
- Maintained minimal volume changes, around a few percent.
- Achieved a decrease in CFD-calculated WSS by approximately 4.2% compared to original geometries.
Conclusions:
- The developed method effectively reduces surface roughness in low-resolution medical images.
- The technique minimizes volume alterations, preserving geometric integrity.
- Improved CFD accuracy for WSS analysis in arteries, enhancing its utility for medical applications.
