發(fā)布時(shí)間：2018-08-11 16:19

【摘要】：超聲波技術(shù)近年來迅速發(fā)展并廣泛應(yīng)用于醫(yī)學(xué)診斷、治療和工業(yè)檢測(cè)領(lǐng)域。與生物組織作用后的超聲波，是反映生物組織性質(zhì)的一個(gè)信息載體。在生物醫(yī)學(xué)超聲基礎(chǔ)研究中，探索超聲波信息載體與生物組織間的聯(lián)系，尋找超聲波中體現(xiàn)組織的一些結(jié)構(gòu)特征參量，一直都是人們研究熱點(diǎn)課題之一。實(shí)際中的超聲診斷技術(shù)，例如超聲診斷儀，探頭從體表接收到的體內(nèi)超聲信號(hào)是淺表軟組織（皮膚、脂肪和肌肉等）、體內(nèi)組織和超聲系統(tǒng)相互作用的結(jié)果，這就為體內(nèi)組織結(jié)構(gòu)特征識(shí)別帶來困難；另一方面，超聲診斷儀獲得的信號(hào)大都是經(jīng)過了檢波處理，是過濾了的信號(hào)，丟失了很多組織性質(zhì)和結(jié)構(gòu)特征信息。因此，，對(duì)于淺表軟組織的超聲檢測(cè)信號(hào)處理，不管從理論還是實(shí)際運(yùn)用來講均應(yīng)屬于研究的熱點(diǎn)。 針對(duì)淺表軟組織結(jié)構(gòu)的超聲檢測(cè)研究并未深入，使得淺表界面結(jié)構(gòu)識(shí)別、定位還不準(zhǔn)確情況，本文提出了“皮膚-淺層脂肪-淺筋膜-深層脂肪-深筋膜-肌肉”的淺表分層結(jié)構(gòu)，利用信號(hào)的卷積模型分析淺表界面信號(hào)特征。研究課題的目的有兩方面，一方面，本文對(duì)淺表軟組織分層結(jié)構(gòu)的超聲檢測(cè)課題，利用信號(hào)處理技術(shù)探討界面的信號(hào)特征提取和識(shí)別；另一方面，研究課題嘗試使用超聲波檢測(cè)技術(shù)研制脂肪厚度測(cè)量?jī)x，測(cè)量人體局部皮下脂肪厚度，從而隨時(shí)檢驗(yàn)運(yùn)動(dòng)和節(jié)食效果，更期望為超聲吸脂提供一種監(jiān)測(cè)手段。 本課題完成的主要工作、成果和創(chuàng)新點(diǎn)總結(jié)有以下幾點(diǎn)： 對(duì)淺表（皮膚、脂肪、筋膜和肌肉）的生物組織特性及結(jié)構(gòu)分布特征進(jìn)行分析，結(jié)合淺表超聲檢測(cè)的射頻回波信號(hào)，找出各反射回波代表的淺層組織界面。利用脈沖反射法測(cè)量界面之間的距離，即各組織層厚度，將測(cè)量結(jié)果與B超診斷儀、直尺作對(duì)比，從而確定組織界面回波，為進(jìn)一步界面信號(hào)特征提取做準(zhǔn)備。 雖然軟組織間的聲阻抗相差不大，但淺表軟組織有其特殊的結(jié)構(gòu)特征，特別是淺筋膜和深筋膜處的界面薄而且界面數(shù)等因個(gè)體不同各異，造成超聲回波在這兩處信號(hào)特征明顯，因此我們可以通過這兩處的回波信號(hào)特征識(shí)別來測(cè)定人體脂肪厚度。 為了提取筋膜界面信號(hào)特征，本文從理論上利用信號(hào)卷積模型對(duì)界面信號(hào)相互疊加效應(yīng)進(jìn)行解釋。在此基礎(chǔ)上，通過Matlab軟件對(duì)信號(hào)卷積模型進(jìn)行模擬驗(yàn)證，并將卷積模型應(yīng)用于離體豬淺表組織界面信號(hào)的特征識(shí)別。實(shí)驗(yàn)結(jié)果證實(shí)了振蕩波數(shù)作為信號(hào)特征識(shí)別參量的可行性。 超聲射頻信號(hào)攜帶了淺表軟組織的大量結(jié)構(gòu)特征信息，但由于探頭發(fā)射波形有一定的持續(xù)時(shí)間以及受檢測(cè)系統(tǒng)的影響，而在實(shí)際淺組織中筋膜界面又相距很近，在界面處反射波就會(huì)不同程度的相互疊加，造成界面波形的不易識(shí)別。本文應(yīng)用小波變換具有恒Q（品質(zhì)因數(shù)）性質(zhì)、對(duì)信號(hào)的時(shí)寬和帶寬的局部分析能力，對(duì)淺表信號(hào)在不同頻率范圍內(nèi)進(jìn)行多分辨分析，實(shí)現(xiàn)了筋膜界面回波的時(shí)域信號(hào)重構(gòu)。從重構(gòu)界面信號(hào)能更清晰看出應(yīng)用振蕩波數(shù)作為界面特征量的可行性，證實(shí)卷積模型解釋信號(hào)疊加的正確性。 本文中的信號(hào)處理方法是第一次應(yīng)用于淺表軟組織結(jié)構(gòu)的超聲檢測(cè)課題，研究工作還未見相關(guān)文獻(xiàn)報(bào)道。實(shí)驗(yàn)卷積模型及其對(duì)振蕩波數(shù)的解釋可用于人體軟組織間界面或其它相似界面結(jié)構(gòu)特征的識(shí)別。離體豬肉脂肪厚度實(shí)驗(yàn)證明儀器能較好的測(cè)量較厚且組織結(jié)構(gòu)均勻的脂肪厚度，而對(duì)于人體腹部實(shí)驗(yàn)，由于呼吸運(yùn)動(dòng)，超聲回波信號(hào)伴隨著噪音干擾，這使得淺表軟組織的回波信號(hào)難以檢測(cè)。如何消除測(cè)量干擾，提高信號(hào)的穩(wěn)定性，是測(cè)量?jī)x器設(shè)計(jì)無論從軟件還是硬件都是進(jìn)一步深入研究的課題。
[Abstract]:Ultrasound technology has developed rapidly in recent years and is widely used in medical diagnosis, treatment and industrial detection. Ultrasound after interaction with biological tissue is an information carrier reflecting the nature of biological tissue. Some structural parameters of tissues have always been one of the hotspots of research. In practice, ultrasonic diagnostic techniques, such as ultrasonic diagnostic apparatus, the ultrasonic signals received by the probe from the body surface are the results of superficial soft tissues (skin, fat, muscle, etc.), the interaction between the tissues in the body and the ultrasonic system, which is the structure of the body. On the other hand, the signals obtained by ultrasonic diagnostic instruments are mostly filtered signals, which lose a lot of information about the nature and structure of tissues.
In view of the fact that the ultrasonic detection of superficial soft tissue structure is not thoroughly studied, which makes the identification and localization of superficial interface structure inaccurate, the superficial layer structure of skin-superficial fat-superficial fascia-deep fat-deep fascia-muscle is proposed in this paper. The convolution model is used to analyze the signal characteristics of superficial interface. There are two aspects. On the one hand, the ultrasonic detection of superficial soft tissue layered structure, using signal processing technology to explore the interface signal feature extraction and recognition; on the other hand, the research topic attempts to use ultrasonic detection technology to develop a fat thickness measurement instrument, measuring the thickness of human local subcutaneous fat, so as to detect movement at any time. And dieting results are more likely to provide a monitoring tool for ultrasound liposuction.
The main tasks, achievements and innovations of this project are summarized as follows:
The biological tissue characteristics and structure distribution characteristics of superficial tissues (skin, fat, fascia and muscle) were analyzed, and the superficial tissue interfaces represented by the reflected echoes were found out by combining with the radio frequency echo signals detected by superficial ultrasound. By contrast, the echo of the tissue interface is determined, so as to prepare for further feature extraction of interface signals.
Although there is little difference in acoustic impedance between soft tissues, superficial soft tissues have their special structural characteristics, especially the thin interface between superficial fascia and deep fascia, and the number of interfaces varies from individual to individual, resulting in the obvious characteristics of ultrasonic echoes in these two places. Therefore, we can identify the characteristics of echo signals at these two places to determine the human body. Fat thickness.
In order to extract the signal characteristics of the fascial interface, the signal convolution model is used to explain the superposition effect of the interface signals in theory. Based on this, the convolution model is simulated and verified by Matlab software, and the convolution model is applied to identify the characteristics of the interface signal of the pig superficial tissue in vitro. The wave number is the feasibility of signal recognition.
Ultrasound radio frequency signal carries a lot of structural information of superficial soft tissue, but the waveform emitted by the probe has a certain duration and is affected by the detection system. In the actual superficial tissue, the fascial interface is very close, and the reflected waves will overlap at the interface to different degrees, which makes the interface waveform difficult to identify. The wavelet transform has the property of constant Q (quality factor) and the ability of local analysis of the time-width and bandwidth of the signal. The superficial signal is analyzed by multi-resolution in different frequency range. The time-domain signal reconstruction of the fascial interface echo is realized. It is proved that convolution model can explain the correctness of signal superposition.
Experimental convolution model and its interpretation of oscillatory wavenumber can be used to identify the structural features of human soft tissue interfaces or other similar interfaces. In vitro pork fat thickness tester It is difficult to detect the echo signal of superficial soft tissue because of the noise disturbance accompanied by breathing movement in abdominal experiment. How to eliminate the measurement interference and improve the stability of the signal is the design of the measuring instrument whether from software or hardware. These are all topics to be further studied.
【學(xué)位授予單位】：重慶醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：R310

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 賈鐳,趙立國,馬洪波,周寶華,宋春梅;B超測(cè)量皮脂厚度的臨床應(yīng)用[J];腸外與腸內(nèi)營養(yǎng);2003年01期

2 張均喜;任慶云;李玉樓;叢力寧;趙君祿;;腹內(nèi)脂肪與血糖血脂的相關(guān)性研究[J];河北醫(yī)藥;2009年15期

3 徐文明,張梅軍,唐建;小波多分辨率分析在信號(hào)奇異性檢測(cè)中的應(yīng)用[J];解放軍理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2002年03期

4 許濤;王立;;超聲檢測(cè)技術(shù)在吸脂術(shù)中的應(yīng)用[J];實(shí)用臨床醫(yī)學(xué);2006年10期

5 張敏貴,周德龍,潘泉,張洪才,張紹武;生物特征識(shí)別及研究現(xiàn)狀[J];生物物理學(xué)報(bào);2002年02期

6 郭建中,魏煒,陳啟敏;非均勻結(jié)構(gòu)軟組織沖激響應(yīng)估計(jì)方法模擬研究[J];陜西師范大學(xué)學(xué)報(bào)(自然科學(xué)版);1996年03期

7 唱文娟,張淼,康春松,王健;皮膚及皮神經(jīng)超聲檢測(cè)的實(shí)驗(yàn)研究[J];山西醫(yī)科大學(xué)學(xué)報(bào);2003年06期

8 步軍;張揚(yáng);陳輝;梁治平;黃結(jié)玲;;CT測(cè)量2型糖尿病患者內(nèi)臟脂肪容積和胰島素抵抗的關(guān)系[J];實(shí)用醫(yī)學(xué)雜志;2009年14期

9 陳慧梅;劉志紅;楊斌;蔡軍;陳燕;王慶文;黎磊石;;肥胖患者體脂分布與腎臟損害的關(guān)系[J];腎臟病與透析腎移植雜志;2006年02期

10 李小娟;王黎;高曉蓉;王澤勇;;超聲無損檢測(cè)成像技術(shù)[J];現(xiàn)代電子技術(shù);2010年21期

相關(guān)會(huì)議論文 前1條

1 周萬松;;超聲波療法的應(yīng)用進(jìn)展[A];2005年全國超聲醫(yī)學(xué)工程學(xué)術(shù)會(huì)議論文集[C];2005年

本文編號(hào)：2177537