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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 生物機電工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58343
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DC 欄位值語言
dc.contributor.advisor周呈霙(Chang-Ying Chou)
dc.contributor.authorHung-Yi Chouen
dc.contributor.author周宏屹zh_TW
dc.date.accessioned2021-06-16T08:11:59Z-
dc.date.available2014-03-09
dc.date.copyright2014-03-09
dc.date.issued2014
dc.date.submitted2014-02-17
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Beck, A. and M.Teboulle. 2009a. Fast gradient-based algorithms for constrainted total variation image denoising and deblurring problems. Image Processing, IEEE Transaction on. 18:2419-2434.
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Chambolle, A. 2004.An algorithm for total variation minimization and applications.Journal of Mathematical Imaging and Vision. 20:89-97.
Kao, C.-M., J. S. Souris, S. Cho, B. C. Penney and C.-T. Chen. 2005.Initial performance evaluation of a modular, large-area detector PET scanner for small animal imaging.In “Nuclear Science Symposium Conference Record, 2005 IEEE”.2081-2084.
Kao, C.-M., Q. Xie, Y.Dong, L. Wan and C.-T. Chen.2009. A High-Sensitivity Small Animal PET Scanner: Development and Initial Performance Measurements”.Nuclear Science, IEEE Transaction on. 56: 2678-2688.
Kao, C.-M. 2008. Windowed image reconstruction for time-of-flight positron tomography.Phys. Med. Bio, 53:3431-3445.
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Kyba, C. Wiener, R. Newcomer,F. Van Berg, R.Dressnandt,N. and Karp,J. 2007. Timing measurements from a TOFPET scanner using local PMT triggering. In“Nuclear Science Symposium and Medical ImagingConference record, 2007”.4123–8.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58343-
dc.description.abstractDual-head small-animal positron emission tomography (DHAPET) has characteristics of high detection sensitivity and flexible system configurations. However, the systemgeometry may result in severe parallax errors and undetected events along the trans-axial directions, thus reducing the image quality.With the advancement of detector hardware, time-of-flight (TOF) of photons can be detected, which has demonstrated significant improvement in image quality, and can greatly benefit its use in research studies and clinics. Algorithms like total variation (TV) minimization methods that aim to compensate the effects of data truncation can be employed to reconstruct images with better resolution and quality. In this work, we will numerically compute the DHAPET system response matrix that includes TOF information and propose a TOF-PET reconstructionalgorithm based on TV-minimization. By applying both TOF information and TV minimization in the iterative algorithm, the reconstructed images can be anticipated to have improved quality with better spatial resolution.en
dc.description.provenanceMade available in DSpace on 2021-06-16T08:11:59Z (GMT). No. of bitstreams: 1
ntu-103-R00631040-1.pdf: 1258523 bytes, checksum: 10acc1cecc95d8fbf5a15115d8705230 (MD5)
Previous issue date: 2014
en
dc.description.tableofcontents誌謝
Abstract
TABLE OF CONTENTS i
LIST OF FIGURES iii
LIST OF TABLES iv
Chapter 1 1
1.1 Background 1
1.2 Frameworks 5
CHAPTER 2 6
2.1 TOF PET and Small Animal PET 6
2.1.1 Positron Emission Tomography 6
2.1.2 Dual-Head Flat-Panel Small Animal PET System 7
2.1.3 Time-of-Flight PET System 9
2.2 Simulation and Reconstruction Algorithms 12
2.2.1 GATE: A Simulation Tool for PET 12
2.2.2 Numerical Methods for PET Image Reconstruction 14
2.2.3 Monte Carlo Simulation 15
2.2.4 Voxel-Based Ray-Tracing Simulation 16
2.2.5 Optimization Algorithm 18
2.2.6 Total Variation Minimization Algorithm 19
Chapter 3 21
3.1 Simulation Flowchart 21
3.2 Instruments 22
3.2.1 System Configuration 22
3.3 Research Methods 23
3.3.1 System Property 23
3.3.2 System Response Matrix 25
3.3.3 Ray-tracing Simulation of TOF-based System Matrix 25
3.3.3 The implement of GPU acceleration 30
3.3.4 Total Variation Algorithm 31
3.3.5 Fast Iterative Shrinkage-Thresholding (FISTA) Algorithm 32
3.3.5 Burring Operator and FISTA De-blurring Model 35
3.3.6 Non-local Means-FISTA (NLM-FISTA) Algorithm 36
CHAPTER 4 38
4.1 Simulation Efficiency of System Response Matrix 38
4.2 Performance of Time-of-Flight 39
4.3 Performance of TV/NLM minimization 43
4.3.1 The performance of TV/NLM- FISTA denoising model 44
4.3.2The performance of TV/NLM FISTA deblurring model 46
CHAPTER 5 49
5.1 Research Summary 49
Reference 50
dc.language.isoen
dc.subject全域變異數最小化zh_TW
dc.subject正子斷層掃描zh_TW
dc.subject時間飛行信息zh_TW
dc.subjectTotal variation constrainten
dc.subjectPositron emission tomographyen
dc.subjectTime-of-flighten
dc.title飛行時間信息與全域變異數最小化在雙平板正子攝影系統的應用與分析zh_TW
dc.titleTime-of-Flight Image Reconstruction for Dual-Head Flat-Panel PET with TV Minimization Constrainten
dc.typeThesis
dc.date.schoolyear102-1
dc.description.degree碩士
dc.contributor.oralexamcommittee蕭穎聰(Ing-Tsung Hsiao),許靖涵(Ching-Han Hsu)
dc.subject.keyword正子斷層掃描,時間飛行信息,全域變異數最小化,zh_TW
dc.subject.keywordPositron emission tomography,Time-of-flight,Total variation constraint,en
dc.relation.page52
dc.rights.note有償授權
dc.date.accepted2014-02-17
dc.contributor.author-college生物資源暨農學院zh_TW
dc.contributor.author-dept生物產業機電工程學研究所zh_TW
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