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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
Authors
Seunghyeon Hwang
DGIST Authors
Hwang, Seunghyeon; Park, SanghyunMoon, Inkyu
Advisor(s)
문인규
Co-Advisor(s)
Sanghyun Park
Issue Date
2020
Available Date
2020-06-23
Degree 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
University
DGIST
Related Researcher
  • Author Moon, Inkyu Intelligent Imaging and Vision Systems Laboratory
  • Research Interests
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Collection:
Department of Robotics EngineeringThesesMaster


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