Ghasemifard Hadi, Behnam Hamid, Tavakkoli Jahan
Department of Biomedical Engineering, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran.
Department of Biomedical Engineering, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.
J Med Signals Sens. 2019 Jan-Mar;9(1):24-32. doi: 10.4103/jmss.JMSS_17_18.
The main goal of ultrasound therapy is to have clinical effects in the tissue without damage to the intervening and surrounding tissues. Treatments have been developed for both in vitro and in clinical applications. HIFU therapy is one of these. Non-invasive surgeries, such as HIFU, have been developed to treat tumors or to stop bleeding. In this approach, an adequate imaging method for monitoring and controlling the treatment is required.
In this paper, an adaptive compressive sensing representation of ultrasound RF echo signals is presented based on empirical mode decomposition (EMD). According to the different numbers of intrinsic mode functions (IMFs) produced by the EMD, the ultrasound signals is adaptively compressive sampled in the source and then adaptively reconstructed in the receiver domains. In this paper, a new application of compressive sensing based on EMD (CS-EMD) in the monitoring of high-intensity focused ultrasound (HIFU) treatment is presented. Non-invasive surgeries such as HIFU have been developed for various therapeutic applications. In this technique, a suitable imaging method is necessary for monitoring of the treatment to achieve adequate treatment safety and efficacy. So far, several methods have been proposed, such as ultrasound radiofrequency (RF) signal processing techniques, and imaging methods such as X-ray, MRI, and ultrasound to monitor HIFU lesions.
In this paper, a CS-EMD method is used to detect the HIFU thermal lesion dimensions using different types of wavelet transform. The results of the processing on the real data demonstrate the potential for this technique in image-guided HIFU therapy.
In this study, a new application of compressive sensing in the field of monitoring of the HIFU treatment is presented. To the best of our knowledge, so far no studies on compressive sensing have been carried out in the monitoring of the HIFU. Based on the results obtained, it was showed that the number of measurements and Intrinsic Mode Functions have the function of noise reduction. In addition, results were shown that the successful reconstruction of the compressive sensing signals can be gained using a threshold based algorithm. To this end, in this paper it was shown that by selecting an suitable number of measurements, the sparse transform, and a thresholding algorithm, we can achieve a more accurate detection of the HIFU thermal lesion size.
超声治疗的主要目标是在不损伤中间和周围组织的情况下对组织产生临床效果。已开发出用于体外和临床应用的治疗方法。高强度聚焦超声（HIFU）治疗就是其中之一。诸如HIFU之类的非侵入性手术已被开发用于治疗肿瘤或止血。在这种方法中，需要一种适当的成像方法来监测和控制治疗。
本文基于经验模态分解（EMD）提出了一种超声射频回波信号的自适应压缩感知表示。根据EMD产生的本征模态函数（IMF）的不同数量，超声信号在源域进行自适应压缩采样，然后在接收域进行自适应重建。本文提出了一种基于EMD的压缩感知（CS-EMD）在高强度聚焦超声（HIFU）治疗监测中的新应用。诸如HIFU之类的非侵入性手术已被开发用于各种治疗应用。在这项技术中，需要一种合适的成像方法来监测治疗，以实现足够的治疗安全性和有效性。到目前为止，已经提出了几种方法，如超声射频（RF）信号处理技术，以及用于监测HIFU损伤的成像方法，如X射线、MRI和超声。
本文使用CS-EMD方法，利用不同类型的小波变换来检测HIFU热损伤尺寸。对真实数据的处理结果证明了该技术在图像引导HIFU治疗中的潜力。
在本研究中，提出了压缩感知在HIFU治疗监测领域的新应用。据我们所知，到目前为止，尚未在HIFU监测中开展关于压缩感知的研究。基于获得的结果，表明测量次数和本征模态函数具有降噪功能。此外，结果表明使用基于阈值的算法可以成功重建压缩感知信号。为此，本文表明通过选择合适的测量次数、稀疏变换和阈值算法，可以更准确地检测HIFU热损伤大小。
