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An Improved SMWI Processing of Substantia Nigra Using Accurate Phase Combination and Deep Neural Network Based QSM : 정확한 위상 합성과 심층 신경망 기반 QSM을 이용한 흑질의 SMWI 영상 개선
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 이종호 | - |
dc.contributor.author | 조민주 | - |
dc.date.accessioned | 2018-12-03T01:33:46Z | - |
dc.date.available | 2018-12-03T01:33:46Z | - |
dc.date.issued | 2018-08 | - |
dc.identifier.other | 000000152431 | - |
dc.identifier.uri | https://hdl.handle.net/10371/143631 | - |
dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2018. 8. 이종호. | - |
dc.description.abstract | Visibility of nigrosome 1, a subregion of substantia nigra is used as an MR imaging biomarker of Parkinsons disease. In this work, we introduced two algorithms for SMWI imaging of substantia nigra. First, we suggested Multi-Channel Phase Combination using Multi-Echo (MCPC-ME), a strategy to calculate and correct phase offsets in multi-echo GRE data. MCPC-ME provided a more accurate estimation of voxel-wise phase offsets particularly in low SNR regions by utilizing phase information from all echoes. Second, we applied QSMnet, a deep neural network for QSM reconstruction, to produce QSM image used in SMWI processing. QSM of nigrosome 1 was reconstructed to have comparable SMWI contrast with 5.4 times faster reconstruction speed compared to the conventional QSM reconstruction algorithm. | - |
dc.description.tableofcontents | 초 록 i
List of Figures iii Chapter 1. Introduction 1 1.1 Introduction 1 1.1.1 Parkinsons disease and SMWI image 1 Chapter 2. Phase Combination using MCPC-ME 5 2.1 Introduction 5 2.2 Background 5 2.2.1 Preliminary 5 2.2.2 MCPC-C 6 2.2.3 MCPC-3D 6 2.2.4 MCPC-ME 7 2.3 Methods 7 2.3.1 Data acquisition 7 2.3.2 Data processing 8 2.3.3 Data analysis 8 2.4 Results 9 2.5 Discussion 17 Chapter 3. SMWI with iLSQR-trained QSMnet 19 3.1 Introduction 19 3.2 Methods 21 3.2.1 Data acquisition 21 3.2.2 QSMnet 22 3.2.3 Data processing 24 3.2.4 Data Analysis 27 3.3 Results 28 3.4 Discussion 36 Chapter 4. Conclusion 42 References 44 Abstract 47 | - |
dc.format | application/pdf | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject.ddc | 621.3 | - |
dc.title | An Improved SMWI Processing of Substantia Nigra Using Accurate Phase Combination and Deep Neural Network Based QSM | - |
dc.title.alternative | 정확한 위상 합성과 심층 신경망 기반 QSM을 이용한 흑질의 SMWI 영상 개선 | - |
dc.type | Thesis | - |
dc.contributor.AlternativeAuthor | Minju Jo | - |
dc.description.degree | Master | - |
dc.contributor.affiliation | 공과대학 전기·정보공학부 | - |
dc.date.awarded | 2018-08 | - |
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