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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, SanghyunHwang, SeunghyeonMoon, 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
DOI
10.22677/Theses.200000285033
Degree
Master
Department
Robotics Engineering
Publisher
DGIST
Related Researcher
  • 박상현 Park, Sang Hyun 로봇및기계전자공학과
  • Research Interests 컴퓨터비전; 인공지능; 의료영상처리
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Department of Robotics and Mechatronics Engineering Theses Master

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