臺灣博碩士論文加值系統

超音波系統廣泛應用於與軟組織相關的病理診斷，對於肌腱部位的評估扮演著重要的角色。肌腱病變是骨科臨床常見的疾病之一，手部肌腱病變的診斷包括狹窄性肌腱滑膜炎、板機指以及網球肘，臨床醫師常藉以測量其肌腱滑移量評估病變與否。然而在肌腱超音波影像序列追蹤上，不止受到超音波斑點雜訊與其他外在因素影響，還包含肌腱本身的纖維結構，使得其運動趨勢與滑移量難以準確的追蹤，並且相當耗時。
為解決上述問題，本篇論文提出兩種以整體運動趨勢為基礎的追蹤演算法，應用於追蹤手肘的伸肌總腱與手指的屈指深肌。在伸肌總腱的部分，由於其運動通常伴隨著骨頭的整體運動，因此第一種方法利用骨頭的整體運動趨勢當作參考，在肌腱部位找到最佳的穩定特徵點，接著找出此特徵點在時間軸上的每個位子，即定義為整個肌腱運動的路徑；而在屈指深肌的部分，單純只有肌腱的運動，因此採用第二種方法，利用光流法的運動當作參考，給予多核心區塊匹配適當的時機點執行，並且利用光流法的運動趨勢當作內插的資訊，得到良好的追蹤結果。
為了驗證方法的正確性，本篇論文藉由大體實驗，在屈指深肌部位埋下鋁片，確認肌腱運動在超音波影像序列上的情形。在手肘的伸肌總腱則是利用人工追蹤的結果來驗證方法，同時利用在大體實驗驗證過的方法來佐證。本篇論文所提出的兩種方法皆可有效的利用整體運動趨勢當作參考來輔佐追蹤結果，並且經由實驗可得之兩種方法皆有可靠並準確的估計肌腱的運動狀況。

Ultrasound system plays an important role in soft tissue examination, which has been widely used in clinical tendinopathy evaluation. In human hands, tendon motion estimation in ultrasound image sequences is of great significance for investigating tendinopathies including trigger finger and tennis elbow. However, the difficulties of tendon motion tracking for ultrasound image sequences not only suffer from temporal decorrelation of speckle patterns, shadow, artifact and other factors but also confused by the hard-tracking fibrous structure of tendons.
Unlike traditional tracking methods which refer to the information of the previous frames or of the first frame only, this study presents two novel strategies based on global motion trend for tendon motion estimation in elbows and fingers to overcome the above-mentioned problems. The first one is a 3-D global trend-based speckle tracking (GTB-ST) scheme, which searches the best speckle feature point for overall tendon position tracking. The second one is an integrated 2-D optical flow trend-based multi-kernel block matching (OFTB-MKBM) scheme with subpixel motion tracking that can handle both small and large displacements at different instantaneous velocities during the entire motion sequence.
Manual tracking in common extensor tendon of elbow and cadaver experiment in flexor digitorum profundus (FDP) tendon of middle finger were measured to validate the accuracies of proposed techniques. Experimental results revealed that the proposed methods are with precise and reliable motion estimation in long B-mode tendon ultrasound image sequences.

Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Related Work 3
1.3 Overview of the Proposed Methods and Thesis Organization 6
Chapter 2 Experimental Materials 8
2.1 Instruments 8
2.2 Experiment Setting for Human Motion 9
2.3 Experiment Setting for Human Cadaver 12
Chapter 3 Global Trend-Based Speckle Tracking (GTB-ST) 14
3.1 System Architecture 15
3.2 Global Motion Path Extraction 15
3.2.1 Bone Positioning 16
3.2.2 Bone Motion Path Segmentation 17
3.3 Optimal Tendon Feature Point Searching 18
3.4 Tendon Motion Path Extraction based on spatiotemporal information 21
Chapter 4 Optical Flow Trend-Based Multi-Kernel Block Matching (OFTB-MKBM) 23
4.1 Optical Flow 24
4.1.1 Optical Flow Concept 25
4.1.2 Optical Flow Estimation for Tendon Motion Tracking 25
4.2 Multi-Kernel Block Matching 29
4.3 Comparison between Optical Flow and Multi-Kernel Block Matching 31
4.4 Optical Flow Trend-Based Multi-Kernel Block Matching 33
Chapter 5 Experimental Results and Discussion 35
5.1 Experimental Results in Finger 35
5.1.1 Evaluation of Ground Truth 35
5.1.2 Evaluation of the Proposed OFTB-MKBM Method 38
5.1.3 Comparison with Other Algorithms 41
5.1.4 Experiments with different MKBM block sizes 44
5.1.5 Experiments with different OF window sizes 47
5.2 Experimental Results in Elbow. 50
5.2.1 Results of the Proposed GTB-ST Method 50
5.2.2 Comparison and Discussion 56
Chapter 6 Conclusion and Future Works 59
6.1 Conclusions 59
6.2 Future Work 60
References 61

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