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Blind Source Separation - Based Motion Detector for Sub-Micrometer, Periodic Displacement in Ultrasonic Imaging
Md Murad Hossain1, Diwash Thapa2, Justin Sierchio2
1Joint Department of Biomedical Engineering, University of North Carolina, Chapel hill, North Carolina, USA.
IEEE International Ultrasonics Symposium : [Proceedings]. IEEE International Ultrasonics Symposium
|December 12, 2017
Summary
Blind source separation (BSS) accurately detects sub-micrometer motion in magnetomotive ultrasound (MMUS) and Shearwave Dispersion Ultrasound Vibrometry (SDUV) imaging. BSS offers superior performance over traditional methods, especially in low signal-to-noise ratio (SNR) conditions.
Area of Science:
- Biomedical Imaging
- Ultrasound Technology
- Signal Processing
Background:
- Magnetomotive ultrasound (MMUS) and Shearwave Dispersion Ultrasound Vibrometry (SDUV) are advanced ultrasound techniques.
- Accurate detection of sub-micrometer periodic motion is crucial for MMUS and SDUV applications.
- Existing motion detection methods may have limitations in low signal-to-noise ratio (SNR) environments.
Purpose of the Study:
- To evaluate the performance of blind source separation (BSS) for sub-micrometer periodic motion detection.
- To compare BSS with frequency-phase locked (FPL) and normalized cross-correlation (NCC) methods in MMUS and SDUV.
- To assess BSS efficacy in low SNR and small displacement scenarios.
Main Methods:
- Implementation of BSS using principal component analysis (PCA) for motion detection.
- Comparative analysis against FPL (for MMUS) and NCC (for SDUV) detectors.
- Validation using in silico models and experimental phantoms for MMUS and SDUV.
Main Results:
- BSS-based MMUS images showed nearly double the SNR compared to FPL at small kernel sizes.
- In SDUV FEM models, BSS-estimated viscoelastic property errors were <10% vs. >20% for NCC at 15 dB SNR.
- BSS-derived shear modulus errors in a phantom were significantly lower (-1.55% to -17.11%) than NCC (29.90% to 244.70%) for displacements ≤ 0.5 μm.
Conclusions:
- BSS is a relevant and effective method for detecting sub-micrometer periodic motion in MMUS and SDUV.
- BSS demonstrates superior performance compared to FPL and NCC, particularly at SNR < 15 dB and displacements < 0.5 μm.
- BSS holds promise for enhancing the accuracy and reliability of quantitative ultrasound techniques.
