Title

Speckle-to-Speckle: Ultrasound speckle reduction technique using unsupervised deep learning

DGIST Authors

Dongkyu Jung ; Jaesok Yu ; Sangyoon Han

Advisor

유재석

Co-Advisor(s)

Sangyoon Han

Issued Date

2022

Awarded Date

2022/08

Citation

Dongkyu Jung. (2022). Speckle-to-Speckle: Ultrasound speckle reduction technique using unsupervised deep learning. doi: 10.22677/thesis.200000629151

Type

Thesis

Subject

Ultrasound, Speckle, Unsupervised learning, Deep learning

Description

Ultrasound, Speckle, Unsupervised learning, Deep learning

Abstract

Table Of Contents

1. INTRODUCTION 1
2. METHODS 5
2.1. Speckle-to-Speckle: Unsupervised learning-based framework 5
2.1.1. Background 5
2.1.2. Speckle-to-Speckle network design 7
2.1.3. Training and inference 8
2.2. Experimental setup 9
2.2.1. Data acquisition 9
2.2.2. Implementation details 11
2.2.3. Evaluation metrics 11
3. RESULTS 15
3.1. Evaluation using training dataset 15
3.2. Evaluation using validation dataset 17
3.3. Evaluation using unspecified dataset 18
3.4. Calculation complexity 20
4. DISCUSSIONS 22
5. CONCLUSION 24
6. REFERENCE 25
요약문 27

URI

http://dgist.dcollection.net/common/orgView/200000629151
http://hdl.handle.net/20.500.11750/16788

DOI

10.22677/thesis.200000629151

Degree

Master

Department

Department of Robotics and Mechatronics Engineering

Publisher

DGIST

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