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研究生: 陳元豪
Chen, Yuan-Hao
論文名稱: 建構一套三維都卜勒超音波影像系統應用於周邊動脈血管疾病篩檢
Development of a 3D Doppler Ultrasound Imaging System for Peripheral Arterial Disease Screening
指導教授: 陳天送
Chen, Tain-Song
學位類別: 碩士
Master
系所名稱: 工學院 - 生物醫學工程學系
Department of BioMedical Engineering
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 68
中文關鍵詞: 主動輪廓偵測都卜勒超音波三維影像重建周邊動脈疾病
外文關鍵詞: active contour mode, Doppler ultrasound, 3D reconstruction, peripheral arterial disease
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  • 近年來,周邊動脈疾病的研究越來越受到重視,其依嚴重程度不同有間歇性跛行、缺血性疼痛、甚至組織壞死而導致截肢等症狀。根據國人十大死因調查,與周邊動脈疾病相關的疾病占了總體死亡的6-12%,因此診斷與監測病患的周邊動脈疾病是非常重要的課題。目前臨床上用來檢測周邊動脈疾病的四種方法有上下肢血壓比、血管攝影術、血管內超音波和核磁共振攝影,主要是以上下肢血壓比來做為主要的診斷方法。近年來有研究指出利用上下肢血壓比來做為周邊動脈疾病的診斷依據被受到討論,當患者有血管方面的疾病而導致血壓產生異狀時,其血壓量測的結果會影響上下肢血壓比診斷的準確度。
    本研究利用三維影像重建並結合都卜勒超音波來提出一個診斷方法應用於周邊動脈疾病的篩檢。在三維影像重建方面,使用25 MHz的雙極性脈衝訊號,並搭配心電圖的R波做為觸發訊號來進行周邊動脈血管B-mode影像掃描,藉由主動輪廓偵測進行血管輪廓的修正,最後利用等值面方法來進行血管三維影像重建。在都卜勒超音波方面,使用五個週期7.5 MHz雙極性脈衝訊號來進行周邊動脈血管血液流速數值偵測,其都卜勒角度設定為75度,脈衝重複頻率設定為20 kHz。在三維影像重建結果方面,此系統可以達到1 frame/s來進行三維影像重建,血管B-mode影像輪廓圈選與實際輪廓誤差值小於10%。在血液流速偵測結果方面,將其結果與商業流速計進行比較,其誤差數值小於11%。在量測周邊動脈疾病患者結果方面,其結果驗證了當周邊動脈血管有阻塞情形發生時會導致血液流速會有異常的狀況發生。此系統相較於商業影像系統降低所需的成本且達到周邊動脈疾病的篩檢,使其應用於周邊動脈疾病患者的早期檢測。

    The study of the peripheral arterial disease (PAD) has gained attention in recent years. There are symptoms of intermittent claudication, ischemic rest pain, and gangrene based on the severity of PAD. According to the top ten leading causes of death in Taiwan, there are 6 to 12 percent of disease is related to PAD. Therefore diagnosis and detection of PAD are important for patients. There are four detection methods widely used for diagnosing PAD in clinics, including ankle brachial pressure index (ABPI), angiography, duplex ultrasonography, and magnetic resonance imaging (MRI). The ABPI is a primary diagnostic method to detect PAD. Recently, it is discussed that the ABPI is used as a reference to diagnose PAD. However, patients with blood vessel disease, distorting the measurement of blood pressure, may affect the results of ABPI diagnosis accuracy.
    In this study, we proposed a method for PAD screening by using 3D image reconstruction and combining with the Doppler ultrasound. In the 3D image reconstruction, we use monocycle 25 MHz bipolar pulse signal, and the R wave of the Electrocardiography (ECG) as a trigger signal to scan the peripheral artery B-mode images. Then, the Active Contour Model (ACM) is used to correct the image contour. Finally, the isosurface function is used to reconstruct 3D image. In Doppler ultrasound, 5-cycle 7.5 MHz bipolar pulse was used to measure the blood flow velocity of peripheral artery with the Doppler angle of 75 degree, and pulse repetition frequency (PRF) of 20 kHz. In 3D image reconstruction, the system reaches 1 frame/s to reconstruct 3D image, and the error of circling blood vessel contour is less than 10%. In blood flow velocity measurement, the error of proposed imaging system compared with commercial instrument is less than 11%. In the results of PAD patients, the results show that blood flow velocity appears abnormal is caused by the obstruction of peripheral arterial in the PAD patient. The cost of proposed imaging system, which is compared with commercial image system, is reduced. This proposed system enables the PAD screening which can be applied for PAD early detection.

    摘要 I Abstract II 誌謝 IV Tables VII Figures VIII Chapter 1 Introduction 1 1.1 Motivation and Objective 1 1.2 Peripheral Arterial Disease (PAD) 2 1.3 Background Reviews 5 1.3.1 Pulse Signal (Doppler) for PAD 5 1.3.2 3D Images 6 1.3.3 Doppler Ultrasound Blood Flow 8 1.4 Applications of High Frequency Ultrasound 11 Chapter 2 Theoretical Basis 16 2.1 Doppler Effects 16 2.1.1 Selecting Range of Doppler Signals 19 2.1.2 The Maximal Flow Velocity Detection 20 2.2 The Introduction of Blood 21 2.2.1 Thrombosis 22 2.2.2 Hemodynamics 22 2.3 3D Image Reconstruction 24 2.3.1 Circle the Contour of B-mode Image 24 2.3.2 Gradient Operation 26 2.3.3 Greedy Method 26 2.3.4 3D Reconstruction 27 2.4 Phase Looked Loop 27 Chapter 3 Materials and Methods 30 3.1 Pulse Signal Design by FPGA 30 3.2 Experimental Setup 35 3.2.1 Flow Tube Experiment 35 3.2.2 In Vivo Experiment 37 3.2.3 Experiment Measurements 38 3.3 Pulse Doppler Signal Processing 39 3.4 System Specifications 41 3.5 3D Image Processing 43 3.5.1 The Methods of Circling Image Contour 44 3.5.2 3D Image Smoothing 46 3.5.3 The Images Combining with Flow Velocity 47 Chapter 4 Results and Discussion 49 4.1 The Results of Image Contour 49 4.1.1 Angle and Iteration Times 50 4.1.2 3D Reconstruction Time 51 4.2 The Results of Flow Tube Experiment 52 4.3 Peripheral Arterial Measurements 59 Chapter 5 Conclusions 64 References 66

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