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Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
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An Optical Flow-Based Approach for Minimally Divergent Velocimetry Data Interpolation
Berkay Kanberoglu1, Dhritiman Das2, Priya Nair3
1School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, 85281, USA.
International Journal of Biomedical Imaging
|March 14, 2019
Summary
This study introduces an optical flow method to improve 3D biomedical image interpolation by reducing anisotropy. The technique leverages fluid velocity data to minimize divergence, enhancing image quality for various applications.
Area of Science:
- Biomedical imaging
- Image processing
- Fluid dynamics
Background:
- Three-dimensional (3D) biomedical image datasets frequently exhibit anisotropy due to differing in-plane and out-of-plane resolutions.
- This anisotropy can negatively impact the accuracy and utility of various image analysis applications.
- Image interpolation techniques are commonly employed to mitigate this issue.
Purpose of the Study:
- To develop an advanced image interpolation framework for 3D biomedical data.
- To specifically address and reduce the detrimental effects of image anisotropy.
- To incorporate fluid velocity information to guide the interpolation process and minimize divergence.
Main Methods:
- A novel optical flow-based framework was developed for image interpolation.
- The method utilizes signals describing fluid flow velocity as additional guidance.
- The framework is designed to minimize divergence within the interpolated image data.
Main Results:
- The proposed optical flow method effectively reduces anisotropy in 3D biomedical images.
- Incorporating fluid velocity data enhances the interpolation accuracy.
- Minimization of divergence leads to more reliable interpolated datasets.
Conclusions:
- The presented optical flow-based framework offers a robust solution for interpolating anisotropic 3D biomedical images.
- This approach improves image quality by reducing anisotropy and divergence.
- The method holds significant potential for enhancing downstream analysis in various biomedical applications.
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