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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Tran, Duc-Tan
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Computer Science & IT Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Improving complex shear modulus imaging quality through enhanced frequency combination techniques Nguyen, Cuong-Thai; Thi Thu Ha, Pham; Duy Phong, Pham; Hai Luong, Quang; Bo Quoc, Bao; Tran, Duc-Tan
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.9033

Abstract

This study aims to improve the accuracy of complex shear modulus imaging (CSMI), a technique used to assess the elasticity and viscosity of soft tissues, essential for analyzing tissue structure and detecting tumors. CSMI methods are primarily divided into quasi-static and dynamic approaches, with the dynamic method estimating the complex shear modulus (CSM) by combining particle velocity measurements with force excitation. However, CSM estimation is vulnerable to errors from noise and the estimation method itself. To address noise, various filtering techniques are commonly applied. Additionally, errors from the estimation process can be minimized using approaches like frequency combination methods. In this research, we introduce an enhanced frequency combination method that substantially increases the accuracy of CSM parameter estimation, leading to higherquality CSMI outcomes. The proposed method achieves the lowest estimation error and the highest Q-index value compared to previous works. The proposed approach offers a valuable advancement in soft tissue imaging, supporting more reliable and precise diagnostic capabilities.
Evaluating random–Nyquist sampling ratios in combined compressed sensing magnetic resonance imaging Khanh Pham, Duc; Tran, Duc-Tan; Quang Tran, Anh
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10333

Abstract

Compressed sensing (CS) has been widely applied in magnetic resonance imaging (MRI) to accelerate the image acquisition without significantly reducing its image quality. In Cartesian MRI, acquisition time can be reduced by skipping phase-encoding steps for faster data acquisition. However, the balance between random under-sampling and Nyquist sampling at the k-space center strongly determines image quality. In this study, we systematically evaluate the impact of different random-to-Nyquist sampling ratios for both single-coil (CS-MRI) and multi-coil (CS-pMRI) reconstructions. Simulation results reveal that dense Nyquist sampling around the k-space center is essential for maintaining image fidelity, whereas reconstruction quality deteriorates sharply when random sampling exceeds approximately 60% of the total under-sampled data. Moreover, CS-pMRI consistently outperforms CS-MRI under equivalent under-sampling factors, benefiting from additional coil sensitivity information that improves resilience against aliasing and noise. These findings provide practical guidelines for hybrid under-sampling design, emphasizing that sufficient Nyquist sampling coverage of central k-space is crucial for achieving high-quality reconstructions while enabling high acceleration in CS-MRI.
Co-Authors Baranitharan, Balakrishnan Bo Quoc, Bao Chandran, Karthik Chowdhury, Subrata Duy Phong, Pham Hai Luong, Quang Khanh Pham, Duc Nguyen Thi, Thu Nguyen, Cuong-Thai Quang Tran, Anh Subramaniyan Mathan, Vaithilingam Thi Thu Ha, Pham