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Updated: Jun 3, 2026

Blood Flow Imaging with Ultrafast Doppler
Published on: October 14, 2020
Enhanced optical flow field of left ventricular motion using quasi-Gaussian DCT filter
Slamet Riyadi1, Mohd Marzuki Mustafa, Aini Hussain
1Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia.
A novel quasi-Gaussian discrete cosine transform (QGDCT) filter enhances optical flow for myocardial motion estimation. This technique reduces speckle noise and improves vector field smoothness, yielding results comparable to physician interpretations.
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Computational Cardiology
Background:
- Accurate left ventricular motion estimation is crucial for diagnosing cardiac abnormalities.
- Optical flow techniques are widely used for motion quantification but struggle with cardiac motion complexity and speckle noise.
- Existing methods often yield non-smooth vector fields, limiting diagnostic accuracy.
Purpose of the Study:
- To introduce a novel quasi-Gaussian discrete cosine transform (QGDCT)-based filter for enhancing optical flow fields.
- To improve myocardial motion estimation by reducing speckle noise and enhancing flow field smoothness.
- To validate the QGDCT filter's performance on both synthetic and clinical echocardiography data.
Main Methods:
- A QGDCT filter was developed, utilizing a customized quasi discrete Gaussian filter with coefficients derived from a 2D DCT.
- The QGDCT filter was applied both before and after optical flow computation to address speckle noise and improve smoothness.
- The algorithm was validated using synthetic echocardiography data simulating myocardial motion and subsequently on clinical echocardiography images.
Main Results:
- Quantitative analysis using magnitude error, angular error, and standard error of measurement demonstrated the filter's effectiveness.
- The QGDCT filter successfully reduced speckle noise and improved the smoothness of the optical flow vector field.
- Motion estimation results obtained using the QGDCT filter showed strong agreement with manual interpretations by physicians.
Conclusions:
- The proposed QGDCT-based filter is an effective tool for enhancing optical flow-based myocardial motion estimation.
- This technique offers a significant improvement over traditional optical flow methods by addressing noise and smoothness issues.
- The QGDCT filter shows promise for improving the accuracy and reliability of cardiac abnormality diagnosis through enhanced motion analysis.
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