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Identification of denatured and normal biological tissues based on compressed sensing and refined composite multi-scale fuzzy entropy during high intensity focused ultrasound treatment |
| Shang-Qu Yan(颜上取)1, Han Zhang(张含)1, Bei Liu(刘备)2, Hao Tang(汤昊)1, and Sheng-You Qian(钱盛友)1,† |
| 1 School of Physics and Electronics, Hunan Normal University, Changsha 410081, China; 2 College of Mathematics and Physics, Hunan University of Arts and Science, Changde 415000, China |
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Abstract In high intensity focused ultrasound (HIFU) treatment, it is crucial to accurately identify denatured and normal biological tissues. In this paper, a novel method based on compressed sensing (CS) and refined composite multi-scale fuzzy entropy (RCMFE) is proposed. First, CS is used to denoise the HIFU echo signals. Then the multi-scale fuzzy entropy (MFE) and RCMFE of the denoised HIFU echo signals are calculated. This study analyzed 90 cases of HIFU echo signals, including 45 cases in normal status and 45 cases in denatured status, and the results show that although both MFE and RCMFE can be used to identify denatured tissues, the intra-class distance of RCMFE on each scale factor is smaller than MFE, and the inter-class distance is larger than MFE. Compared with MFE, RCMFE can calculate the complexity of the signal more accurately and improve the stability, compactness, and separability. When RCMFE is selected as the characteristic parameter, the RCMFE difference between denatured and normal biological tissues is more evident than that of MFE, which helps doctors evaluate the treatment effect more accurately. When the scale factor is selected as 16, the best distinguishing effect can be obtained.
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Received: 16 September 2020
Revised: 26 October 2020
Accepted manuscript online: 02 December 2020
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PACS:
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87.85.-d
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(Biomedical engineering)
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05.45.-a
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(Nonlinear dynamics and chaos)
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| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 11774088 and 11474090). |
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Corresponding Authors:
†Corresponding author. E-mail: shyqian@hunnu.edu.cn
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Cite this article:
Shang-Qu Yan(颜上取), Han Zhang(张含), Bei Liu(刘备), Hao Tang(汤昊), and Sheng-You Qian(钱盛友) Identification of denatured and normal biological tissues based on compressed sensing and refined composite multi-scale fuzzy entropy during high intensity focused ultrasound treatment 2021 Chin. Phys. B 30 028704
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