Open AccessCombination of variational mode decomposition and coherent factor for ultrasound computer tomography
Author(s) -
Shanshan Wang,
Xinyi Zou,
Liang Zeng,
Junjie Song,
Liang Zhou,
Mingyue Ding,
Ming Yuchi
Publication year - 2022
Publication title -
technology and health care
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.281
H-Index - 44
eISSN - 1878-7401
pISSN - 0928-7329
DOI - 10.3233/thc-228016
Subject(s) - imaging phantom , image quality , signal to noise ratio (imaging) , computer science , noise (video) , artificial intelligence , physics , optics , image (mathematics)
BACKGROUND: Ultrasound computed tomography (USCT) is a promising technique for improving the detection of breast cancer. Image quality of USCT has a major impact on the breast cancer diagnosis. OBJECTIVE: This paper investigates the combination of variational mode decomposition (VMD) and coherent factor method for USCT image quality enhancement. METHODS: The signals can be decomposed into multiple intrinsic mode functions (IMFs) sifting through the frequency by VMD method. Refactoring the remaining IMFs, spatio-temporally smoothed coherence factor (STSCF) beamforming method is applied to reconstructed data for USCT. RESULTS: The validation of combination the VMD and STSCF is described through the breast phantom experiment and in vivo experiments. The evaluation indicators such as contrast ratio (CR), contrast to noise ratio (CNR) and signal to noise ratio (SNR) have been better improved in the experimental results. For the breast phantom, the proposed method gives a higher resolution and the better contrast properties for the hyperechoic cyst. The borders of cysts and tumors in the breast phantom can be distinguished clearly. For volunteer breast experiments, artifacts are removed more efficiently while the clutters are suppressed simultaneously. CONCLUSION: The combination of VMD and STSCF can further reduce the noise and suppress the side lobes.