||An Acoustic Tracking System for Medical Ultrasound Image Simulator
||Department of BioMedical Engineering
Position sensing system
超音波在目前的醫學檢測中佔有不可取代的地位。然而超音波檢測取決於醫療檢測人員的技術以及經驗。近年來醫療用超音波模擬器被廣泛應用於協助訓練醫療人員以及醫學背景之學生。當檢測人員移動模擬超音波探頭時，模擬器可提供相對應位置的超音波二維影像，此一方法協助了接受訓練的檢測人員再進入職場前之練習。不同疾病之超音波影像可以備儲存於模擬器中，以提供訓練人員在訓練時做選擇。在超音波模擬器中，感測系統為超音波模擬器中不可或缺的一項技術，高靈敏度的感測系統可提供模擬器好的表現。近期各種各測器應用於超音波模擬器已經問世，例如:磁感應、光學感應、無線射頻辨識(RFID)。本研究以超音波探頭研發出一套位置偵測系統，進而應用於超音波模擬器。系統驗證中則以豬心做為結果呈現。研究中所使用空氣耦合試探頭做為感測器，而探頭又分為激發端與接收端，探頭直徑為 8.4mm，操作頻率為40K Hz。虛擬探頭是以5個空氣耦合試探頭所組成，而模擬平台則是以25個探頭排列成5*5的矩陣。由於虛擬探頭音位置的不同，導致再模擬平台上的矩陣再接收到訊號後輸出的矩陣也不同，進而由資料庫中選擇出最為符合目前位置的超音波二維影像，並顯示在螢幕上。資料庫中的影像是以商用超音波儀器是先截取並儲存。系統的軸向解析度與側向解析度均為0.7mm/frame。而系統旋轉解析度為0.5 degree/frame。在生物體外實驗中，模擬器可以準確的顯示目前量測位置之影像。
Ultrasound has become a standard procedure in clinical examinations. However, Ultrasound examination depends highly on the technique of the operator. Recently, the ultrasound image simulator has been proposed to assist training procedure in hospital and medical school. As operator moves the ultrasound probe on the manikin, simulator provides virtual images for real examination environments, allowing users to practice their skill before clinical diagnosis. A large number of clinical ultrasound data can be stored in simulator as a database for training purpose, particularly for rare disorders. The tracking system is the most crucial part of simulator because a high sensitivity sensing provides a higher performance for displaying the real image. Currently, several commercial ultrasound simulators are available based on different sensors, like electromagnetic, optical, and inertial sensing. In present study, ultrasound sensors are used to develop an ultrasound simulator. System verification is performed by in vitro porcine heart images. The sensors used in this study are air-coupled transducers. One transmit signal and the other receive signal. The diameter of the sensor is 8.4 mm and the operational frequency is 40 kHz. Five transmitting sensors are arranged in 1-D array to transmit the ultrasound signal and 25 receiving sensors are arranged into 5 by 5 2-D array to receive the signal. Since the sequences of receiving signal changes due to the motion of transmitting 1-D array, the position and orientation of the sham probe can be detected precisely by this acoustic sensing system. After the sham probe is positioned, the corresponding ultrasound image is displayed frame by frame according to the real examination environments. The database images are pre-captured using a commercial ultrasound system (Terason t3000). Both sequence of receiving signal and its corresponding image are displayed on the monitor. The lateral and axial resolution of this acoustic sensing system are about 0.7mm/frame and the rotation is about 0.5 degree/frame. The in vitro porcine heart experiment shows that the simulator can display the heart structure precisely confirmed by a well training operator.
Chapter 1 Introduction 14
1.1 Background 14
1.2 Ultrasound Simulation 16
1.3 Literature Reviews 18
1.4 Motivations and Purpose 22
Chapter 2 Basic Theory 23
2.1 Fundamentals of Acoustic Propagation 23
2.1.1 Stress and Strain Relationships 24
2.1.2 Compressional Wave of Ultrasound 26
2.1.3 Characteristic Impedance 27
2.1.4 Attenuation 28
2.2 Ultrasound Transducer 29
2.2.1 Piezoelectric Effect 29
2.2.2 Piezoelectric Constitutive Equation 30
2.2.3 Ultrasonic Transducers 21
2.3 Tracking Devices 34
2.3.1 Electromagnetic Tracking Sensor 34
2.3.2 Optical Tracking Sensor 37
2.3.3 Inertial Tracking Sensor 39
2.3.4 Haptic Devices 40
Chapter 3 Materials and Methods 43
3.1 System Hardware Description 44
3.1.1 Transmitter and Receiver Circuits Design 45
3.1.2 Data Acquisition System 50
3.2 System Software Description 51
3.2.1 Signal Processing Procedure 51
3.2.2 Graphical User Interface 53
3.3 Experimental Setup 54
3.3.1 Commercial Phantom 54
3.3.2 Gelatin Phantom 55
3.3.3 Porcine Heart 56
Chapter 4 Results and Discussions 58
4.1 Experimental Setup 58
4.1.1 Hardware Results 58
4.1.2 Software Results 61
4.2 Experimental Results 61
4.2.1 Phantom Images 61
4.2.2 System Verification 63
4.3 System Limitations 64
Chapter 5 Conclusion and Future Work 65
5.1 Conclusion 65
5.2 Future Work 67
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