New phase unwrapping approach in digital holographic microscopy with deep learning
- Title
- New phase unwrapping approach in digital holographic microscopy with deep learning
- Author(s)
- Seunghyeon Hwang
- DGIST Authors
- Park, Sanghyun ; Hwang, Seunghyeon ; Moon, Inkyu
- Advisor
- 문인규
- Co-Advisor(s)
- Sanghyun Park
- Issued Date
- 2020
- Awarded Date
- 2020-02
- Type
- Thesis
- Description
- Digital holography microscopy, Phase unwrapping, Deep learning, Generative adversarial network.
- Table Of Contents
-
Ⅰ. INTRODUCTION 1
1.1 Introduction 1
1.2 Related works 5
Ⅱ. Digital holographic microscopy 6
2.1 Label-free off-axis digital holographic imaging 6
Ⅲ. Method 9
3.1 Generation of dataset 9
3.2 Model Architecture 11
3.3 Objective function 13
3.4 Implementation Details 13
Ⅳ. Results 14
4.1 Experimental results 14
4.2 Performance of model for cells of the same and different type as training data 14
4.3 Performance of wrapped phase images with unfocused cells 15
4.4 Unwrapping time with QG, LS, TIE and the proposed model 17
Ⅴ. DISCUSSION AND CONCLUSION 18
5.1 Conclusion 18
Ⅵ. Acknowledgment 18
- URI
-
http://dgist.dcollection.net/common/orgView/200000285033
http://hdl.handle.net/20.500.11750/11976
- Degree
- Master
- Department
- Robotics Engineering
- Publisher
- DGIST
- Related Researcher
-
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Park, Sang Hyun 로봇및기계전자공학과
- Research Interests 컴퓨터비전; 인공지능; 의료영상처리
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- Files in This Item:
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- Appears in Collections:
- Department of Robotics and Mechatronics Engineering Theses Master
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