{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:27:49Z","timestamp":1760956069705,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,8,27]],"date-time":"2020-08-27T00:00:00Z","timestamp":1598486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Identification of denatured biological tissue is crucial to high-intensity focused ultrasound (HIFU) treatment, which can monitor HIFU treatment and improve treatment efficiency. In this paper, a novel method based on compressed sensing (CS) and improved multiscale dispersion entropy (IMDE) is proposed to evaluate the complexity of ultrasonic scattered echo signals during HIFU treatment. In the analysis of CS, the method of orthogonal matching pursuit (OMP) is employed to reconstruct the denoised signal. CS-OMP can denoise the ultrasonic scattered echo signal effectively. Comparing with traditional multiscale dispersion entropy (MDE), IMDE improves the coarse-grained process in the multiscale analysis, which improves the stability of MDE. In the analysis of simulated signals, the entropy value of the IMDE method has less fluctuation compared with MDE, indicating that the IMDE method has better stability. In addition, MDE and IMDE are applied to the 300 cases of ultrasonic scattered echo signals after denoising (including 150 cases of normal tissues and 150 cases of denatured tissues). The experimental results show that the MDE and IMDE values of denatured tissues are higher than normal tissues. Both the MDE and IMDE method can be used to identify whether biological tissue is denatured. However, the multiscale entropy curve of IMDE is smoother and more stable than MDE. The interclass distance of IMDE is greater than MDE, and the intraclass distance of IMDE is less than MDE at different scale factors. This indicates that IMDE can better distinguish normal tissues and denatured tissues to obtain more accurate clinical diagnosis during HIFU treatment.<\/jats:p>","DOI":"10.3390\/e22090944","type":"journal-article","created":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T09:17:08Z","timestamp":1598606228000},"page":"944","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Identification of Denatured Biological Tissues Based on Compressed Sensing and Improved Multiscale Dispersion Entropy during HIFU Treatment"],"prefix":"10.3390","volume":"22","author":[{"given":"Bei","family":"Liu","sequence":"first","affiliation":[{"name":"College of Mathematics and Physics, Hunan University of Arts and Science, Changde 415000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Runmin","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziqi","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Mathematics and Physics, Hunan University of Arts and Science, Changde 415000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingjie","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.eururo.2015.06.018","article-title":"Focal High-intensity Focused Ultrasound Targeted Hemiablation for Unilateral Prostate Cancer: A Prospective Evaluation of Oncologic and Functional Outcomes","volume":"69","author":"Feijoo","year":"2016","journal-title":"Eur. Urol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1148\/radiol.2017161640","article-title":"High-Intensity Focused Ultrasound for Treatment of Symptomatic Benign Thyroid Nodules: A Prospective Study","volume":"284","author":"Lang","year":"2017","journal-title":"Radiology"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4324","DOI":"10.1039\/C5NR08292G","article-title":"Nanoparticle-enhanced synergistic HIFU ablation and transarterial chemoembolization for efficient cancer therapy","volume":"8","author":"You","year":"2016","journal-title":"Nanoscale"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1134\/1.1591291","article-title":"Physical mechanisms of the therapeutic effect of ultrasound (a review)","volume":"49","author":"Bailey","year":"2003","journal-title":"Acoust. Phys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1298","DOI":"10.1080\/02656736.2018.1433880","article-title":"Factors influencing thermal injury to skin and abdominal wall structures in HIFU ablation of uterine fibroids","volume":"34","author":"Yin","year":"2018","journal-title":"Int. J. Hyperth."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"27","DOI":"10.3109\/02656736.2013.860241","article-title":"Temperature-density hysteresis in X-ray CT during HIFU thermal ablation: Heating and cooling phantom study","volume":"30","author":"Weiss","year":"2014","journal-title":"Int. J. Hyperth."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"119","DOI":"10.3109\/02656736.2014.883466","article-title":"Non-invasive temperature monitoring and hyperthermic injury onset detection using X-ray CT during HIFU thermal treatment in ex vivo fatty tissue","volume":"30","author":"Weiss","year":"2014","journal-title":"Int. J. Hyperth."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1007\/s00330-009-1520-5","article-title":"Prostate cancer transrectal HIFU ablation: Detection of local recurrences using T2-weighted and dynamic contrast-enhanced MRI","volume":"20","author":"Girouin","year":"2010","journal-title":"Eur. Radiol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1002\/nbm.1563","article-title":"Real-time volumetric MRI thermometry of focused ultrasound ablation in vivo: A feasibility study in pig liver and kidney","volume":"24","author":"Quesson","year":"2011","journal-title":"NMR Biomed."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.7863\/jum.2010.29.12.1787","article-title":"Correlations between B-mode ultrasonic image texture features and tissue temperature in microwave ablation","volume":"29","author":"Yang","year":"2010","journal-title":"J. Ultrasound Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1080\/02656730600661149","article-title":"Thermal monitoring: Invasive, minimal-invasive and non-invasive approaches","volume":"22","author":"Wust","year":"2006","journal-title":"Int. J. Hyperth."},{"key":"ref_12","unstructured":"Seip, R., Tavakkoli, J., Carlson, R.F., and Wunderlich, A. (2002, January 8\u201311). High-intensity focused ultrasound(HIFU) multiple lesion imagine: Comparison of detection algorithms for real-time treatment control. Proceedings of the 2002 IEEE Ultrasonics Symposium, Munich, Germany."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1111\/cpf.12636","article-title":"Ultrasound image resolution influences analysis of skeletal muscle composition","volume":"40","author":"Paris","year":"2020","journal-title":"Clin. Physiol. Funct. Imaging"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"163","DOI":"10.3109\/02656736.2015.1009180","article-title":"Thermometry and ablation monitoring with ultrasound","volume":"31","author":"Lewis","year":"2015","journal-title":"Int. J. Hyperth."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1177\/0954411914554438","article-title":"A survey of ultrasound elastography approaches to percutaneous ablation monitoring","volume":"228","author":"Zhou","year":"2014","journal-title":"Proc. Inst. Mech. Eng. Part H J. Eng. Med."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1016\/j.ultrasmedbio.2018.03.002","article-title":"Hepatic Steatosis Assessment with Ultrasound Small-Window Entropy Imaging","volume":"44","author":"Zhou","year":"2018","journal-title":"Ultrasound Med. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","article-title":"The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis","volume":"454","author":"Huang","year":"1998","journal-title":"Proc. R. Soc. A Math. Phys. Eng. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1954","DOI":"10.1016\/j.jacc.2004.10.080","article-title":"Detection of Lipid-Laden Atherosclerotic Plaque by Wavelet Analysis of Radiofrequency Intravascular Ultrasound Signals: In vitro validation and preliminary in vivo application","volume":"45","author":"Murashige","year":"2005","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"93","DOI":"10.4310\/CMS.2010.v8.n1.a6","article-title":"Fast linearized Bregman iteration for compressive sensing and sparse denoising","volume":"8","author":"Dong","year":"2010","journal-title":"Commun. Math. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Bai, L., Maechler, P., Muehlberghuber, M., and Kaeslin, H. (2012, January 9\u201312). High-speed compressed sensing reconstruction on FPGA using OMP and AMP. Proceedings of the 2012 19th IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2012), Seville, Spain.","DOI":"10.1109\/ICECS.2012.6463559"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1088\/0031-9155\/56\/1\/014","article-title":"Multi-frequency characterization of the speed of sound and attenuation coefficient for longitudinal transmission of freshly excised human skulls","volume":"56","author":"Pichardo","year":"2010","journal-title":"Phys. Med. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.ultrasmedbio.2003.09.003","article-title":"Attenuation of porcine tissues in vivo after high-intensity ultrasound treatment","volume":"30","author":"Zderic","year":"2004","journal-title":"Ultrasound Med. Biol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Seip, R., Ebbini, E.S., O\u2019Donnell, M.B., and Cain, C. (November, January 31). Non-invasive detection of thermal effects due to highly focused ultrasonic fields. Proceedings of the 1993 IEEE Ultrasonics Symposium, Baltimore, MD, USA.","DOI":"10.1109\/ULTSYM.1993.339611"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"7427","DOI":"10.1088\/0031-9155\/61\/20\/7427","article-title":"The effect of temperature dependent tissue parameters on acoustic radiation force induced displacements","volume":"61","author":"Suomi","year":"2016","journal-title":"Phys. Med. Biol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"91","DOI":"10.4103\/2228-7477.181032","article-title":"Radio Frequency Ultrasound Time Series Signal Analysis to Evaluate High-intensity Focused Ultrasound Lesion Formation Status in Tissue","volume":"6","author":"Mobasheri","year":"2016","journal-title":"J. Med. Signals Sensors"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Tsui, P.-H., and Wan, Y.-L. (2016). Effects of Fatty Infiltration of the Liver on the Shannon Entropy of Ultrasound Backscattered Signals. Entropy, 18.","DOI":"10.3390\/e18090341"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"028702","DOI":"10.7498\/aps.68.20181772","article-title":"Recognition of denatured biological tissue based on variational mode decomposition and multi-scale permutation entropy","volume":"68","author":"Liu","year":"2019","journal-title":"Acta Phys. Sin."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"022911","DOI":"10.1103\/PhysRevE.87.022911","article-title":"Weighted-permutation entropy: A complexity measure for time series incorporating amplitude information","volume":"87","author":"Fadlallah","year":"2013","journal-title":"Phys. Rev. E"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.3390\/e15031069","article-title":"Time Series Analysis Using Composite Multiscale Entropy","volume":"15","author":"Wu","year":"2013","journal-title":"Entropy"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/LSP.2016.2542881","article-title":"Dispersion Entropy: A Measure for Time-Series Analysis","volume":"23","author":"Rostaghi","year":"2016","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, Z., Li, Y., Zhang, K., and Guo, J. (2019). A Novel Improved Feature Extraction Technique for Ship-Radiated Noise Based on IITD and MDE. Entropy, 21.","DOI":"10.3390\/e21121215"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Shang, H., Li, F., and Wu, Y. (2019). Partial Discharge Fault Diagnosis Based on Multi-Scale Dispersion Entropy and a Hypersphere Multiclass Support Vector Machine. Entropy, 21.","DOI":"10.3390\/e21010081"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Azami, H., Fern\u00e1ndez, A., and Escudero, J. (2019). Multivariate Multiscale Dispersion Entropy of Biomedical Times Series. Entropy, 21.","DOI":"10.3390\/e21090913"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2872","DOI":"10.1109\/TBME.2017.2679136","article-title":"Refined Composite Multiscale Dispersion Entropy and its Application to Biomedical Signals","volume":"64","author":"Azami","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.knosys.2018.09.004","article-title":"Intelligent fault diagnosis of rotating machinery using improved multiscale dispersion entropy and mRMR feature selection","volume":"163","author":"Yan","year":"2019","journal-title":"Knowl. Based Syst."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/22\/9\/944\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:03:56Z","timestamp":1760177036000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/22\/9\/944"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,27]]},"references-count":35,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["e22090944"],"URL":"https:\/\/doi.org\/10.3390\/e22090944","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2020,8,27]]}}}