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研究生: 林音妮
Tifany Inne Halim
論文名稱: 基於深度學習方法之超音波影像特徵表示和分類效能增強
Feature Representation and Classification Performance Enhancement in Ultrasound Images Based on Deep Learning Methods
指導教授: 徐勝均
Sendren Sheng-Dong Xu
口試委員: 柯正浩
Cheng-Hao Ko
李俊賢
Jin-Shyan Lee
學位類別: 碩士
Master
系所名稱: 工程學院 - 自動化及控制研究所
Graduate Institute of Automation and Control
論文出版年: 2020
畢業學年度: 108
語文別: 英文
論文頁數: 79
中文關鍵詞: 超音波影像影像處理深度學習
外文關鍵詞: Ultrasound images, image processing, deep learning
相關次數: 點閱:273下載:0
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Acknowledgements I 摘要 II Abstract III Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Thesis Objective 8 1.3 Thesis outline 8 Chapter 2 Ultrasound Image Dataset 9 2.1 Liver Fatty Dataset 9 2.2 Mendeley Breast Cancer Dataset 10 2.3 Baheya Breast Cancer Dataset 10 Chapter 3 Data Augmentation 12 3.1 Introduction to Data Augmentation 12 3.2 Generative Adversarial Network 13 3.3 WGAN-GP 15 3.4 InfoGAN 16 3.5 Customized InfoGAN 18 Chapter 4 Classification 19 4.1 Convolutional Neural Network 19 4.2 ResNet 24 4.2.1 Residual Learning 25 4.2.2 Identity Mapping 26 4.3 DenseNet 27 Chapter 5 Experimental Results and Discussion 29 5.1 Performance Evaluation 29 5.1.1 Sensitivity 30 5.1.2 Specificity 30 5.1.3 Accuracy 31 5.2 Results and Discussion 31 5.2.1 Classification Results with Generated Data 31 5.2.1.1 Training Performance 35 5.2.1.1.1 Liver Fatty Dataset 35 5.2.1.1.2 Mendeley Breast Cancer Dataset 38 5.2.1.1.3 Baheya Breast Cancer Dataset 42 5.2.1.2 Testing Performance 45 5.2.1.2.1 Liver Fatty Dataset 46 5.2.1.2.2 Mendeley Breast Cancer Dataset 47 5.2.1.2.3 Baheya Breast Cancer Dataset 48 5.2.2 Feature Representation 50 5.2.2.1 Liver Fatty Dataset 50 5.2.2.2 Mendeley Breast Cancer Dataset 52 5.2.2.3 Baheya Breast Cancer Dataset 54 Chapter 6 Conclusion and Future Work 57 6.1 Conclusion 57 6.2 Future Work 58

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