Variational mode decomposition for ultrasound computed tomography

Shanshan Wang; Liang Zeng; Junjie Song; Liang Zhou; Mingyue Ding; Ming Yuchi

doi:10.1117/12.2549161

16 March 2020 Variational mode decomposition for ultrasound computed tomography

Shanshan Wang, Liang Zeng, Junjie Song, Liang Zhou, Mingyue Ding, Ming Yuchi

Proceedings Volume 11319, Medical Imaging 2020: Ultrasonic Imaging and Tomography; 113190O (2020) https://doi.org/10.1117/12.2549161
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

In recent years, Ultrasound computed tomography (USCT) has important clinical application prospect in breast cancer screening and early diagnosis. In this paper, the biomedical image denoising technique based on variational mode decomposition (VMD) method for USCT is investigated. The VMD method allows decomposition of data into a finite number of intrinsic mode functions (IMFs) after a sifting pre-process. Removing the noise components and refactoring the remaining IMFs, the processed data can be used for USCT image reconstruction. It can provide images with less noises, higher resolution and better contrast compared to the traditional B-mode imaging method. The validation of VMD method for USCT is presented through the breast phantom experiment. The radio-frequency (RF) data of the breast phantom were captured by the USCT system developed in the Medical Ultrasound Laboratory. The main components of USCT system are data acquisition module and a 1024-element ring array with center frequency 2.5MHz. Graphics processing units (GPUs) have been highly applied to image reconstruction considering its high parallel computation ability. Experimental results show that the reconstructed image of breast phantom by the VMD method get the higher signal to noise ratio (SNR) and more homogeneous background compared to the delay and sum (DAS) method. The contrast ratio (CR) could be enhanced from 0.96 dB to 1.01dB and 88.38 dB to 99.53 dB at different regions of interest (ROI). The contrast to noise ratio (CNR) enhance from 0.09dB to 0.13dB at hypoechoic area and from 8.01 to 13.03 at hyperechoic area.

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Shanshan Wang, Liang Zeng, Junjie Song, Liang Zhou, Mingyue Ding, and Ming Yuchi "Variational mode decomposition for ultrasound computed tomography", Proc. SPIE 11319, Medical Imaging 2020: Ultrasonic Imaging and Tomography, 113190O (16 March 2020); https://doi.org/10.1117/12.2549161

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KEYWORDS

Ultrasonography

Computed tomography

Chromium

Breast

Image restoration

Signal to noise ratio

Image quality

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