Medical imaging system is to provide a visual representation of anatomical structures, blood flow velocity, and other diagnostic information. Currently, the mainly three applications in ultrasound system are B-mode image processing, color Doppler, or spectral Doppler. B mode image represents the power of the received echo. The Doppler mode is used for blood flow estimation and cardiac muscle observation. In this thesis, we focus on B mode imaging. Since the natural characteristics of the propagation wave, beamforming thus play a vital role in array signal processing, whose functionality is to focus the received echoes. Beamforming can be performed by real aperture and synthetic aperture with corresponding ways of delay calculation to focus echoes. The oldest but the most popular method is to delay and sum for received echoes alignment, which we adopt in this work. Real aperture use full array, which consumes more power and computation complexity to form an image. Synthetic aperture uses less hardware overhead in trade of image quality. High frame rate imaging system (HFR) is just composed of synthetic transmit aperture and broad transmit beams (plane wave, defocused beams, and diffraction beams).
The techniques of digital signal processing can overcome this problem by weighting adjustment on channels. Methods of constant weighting are often used to beam shaping; however, adaptive methods are also applied to medical signal processing recently. For example, CFMVDR aims to enhance terrible image quality in HFR system. The problem is the high complexity of weighing calculation.
In this thesis, we propose a new method of low complexity adaptive imaging. This method has little hardware overhead without performance loss. We have built the proposed model on Matlab to test the efficacy by both synthetic data using Field II and clinical data of breast from female patients. Still, we implement the proposed adaptive beamforming on CUDA (Compute Unified Device Architecture, new platform of multi-core computing) and propose some methods of modification. In the assistance of multi-core platform, the proposed adaptive imaging can be proven to approach the requirement of real time application, which is ever published. Through this thesis, we offer the new concepts combined with adaptive algorithms and implementations for future research in this domain.

List of Figures ix
List of Tables xiii
Chapter 1 Introduction 1
1.1 Overview of Ultrasonic Imaging Systems 1
1.2 Research Topics and Main Contributions 10
1.3 Thesis Organization 17
Chapter 2 High Frame Rate (HFR) Imaging Systems 18
2.1 Principles of Medical Ultrasound 18
2.2 High Frame Rate Imaging System 32
2.3 Summary 35
Chapter 3 Review of Adaptive Beamforming Algorithms 36
3.1 Coherence Factor (CF) and Generalized CF (GCF) 38
3.2 Minimum Variance Directionless Responese (MVDR) 43
3.3 CFMVDR in HFR System 47
3.4 Summary 51
Chapter 4 Proposed Adaptive Algorithm in HFR System 53
4.1 Algorithm Description 53
4.2 Complexity Analysis 58
4.3 Simulation Results 60
4.4 Experimental Investigation 64
4.5 Temporal Smoothing Analysis 70
4.6 Summary 80
Chapter 5 Implementation on Multi-core System 81
5.1 Programming Model 81
5.2 Computation Units and Memory Hierarchy 82
5.3 GPU Specification of GTX 260 88
5.4 Parallelism Analysis 89
5.5 Bottleneck Analysis 92
5.6 Emulation Outcome 96
5.7 Summary 97
Chapter 6 Conclusions 99
6.1 Main Contribution 99
6.2 Future Direction 99
Reference 101

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