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研究生:林德銘
研究生(外文):Te-Ming Lin
論文名稱:指紋磁振造影中評估訊號收取次數與參數圖譜精密度的方法
論文名稱(外文):A method to evaluate the relationship between signal acquisition number and parametric mapping precision in MR fingerprinting
指導教授:鍾孝文
指導教授(外文):Hsiao-Wen Chung
口試委員:趙梓程蔡尚岳林發暄曾文毅
口試委員(外文):Tzu-Cheng ChaoShang Yueh TsaiFa-Hsuan LinWen-Yih Isaac Tseng
口試日期:2015-05-26
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:生醫電子與資訊學研究所
學門:工程學門
學類:生醫工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:英文
論文頁數:42
中文關鍵詞:指紋磁振造影參數圖譜參數圖譜精密度脈衝序列最佳化
外文關鍵詞:Magnetic resonance fingerprintingParametric mappingMapping precisionPulse sequence optimization
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指紋磁振造影是一項同時定量多種磁振造影參數的新方法。其利用一系列隨機的射頻脈衝序列,使不同組織產生不同的信號,再利用模式辨認方法,將量測到的信號與事先模擬的信號字典進行比對,進而得到組織的參數。
在指紋磁振造影中,信號量測的次數影響最終的信號長度。信號長度越長,信號字典越大,實驗所需的時間與電腦計算的複雜度都會隨之增加。然而,當信號量測次數減少,參數圖譜的精確度也會隨之改變。為了設計出理想的脈衝序列,我們需要一種評估精確度的方法。
在本篇論文中,我們提出一項參數映射變異指標,可以用以反應參數圖譜的精確度。此外,這個指標可以在掃描前預測參數圖譜精確度隨不同信號收取次數的變化,進而提供實驗前脈衝序列設計參考。

MR Fingerprinting (MRF) is a novel technique to quantify multiple MR parameters simultaneously. A train of pseudorandomized radiofrequency (RF) excitations are used to generate unique signal evolution for different tissues, followed by matching the measured signals to a pre-established dictionary.
The signal acquisition number in MRF is related to the signal length. Longer signals and larger dictionaries increase the scan time and computational complexity. However, as the signal acquisition reduces, the mapping precision also changes. Therefore, for designing an efficient MRF sequence, a method to evaluate the precision change is necessary.
In this thesis, we propose a mapping variation index to reflect the mapping precision in MRF. Besides, this index can predict the precision change under different signal acquisition numbers before MRF scans and provide a reference for sequence designers to modify the signal acquisition number.

致謝 ................................................................. I
中文摘要 ............................................................ II
Abstract............................................................ III
Table of Figures..................................................... VI
Chapter 1 Introduction................................................ 1
1.1 Problem statement................................................. 1
1.2 Thesis outline.................................................... 2
Chapter 2 Background.................................................. 3
2.1 Principles of MR fingerprinting................................... 3
2.2 Signal simulation................................................. 6
2.3 Dictionary matching............................................... 7
2.3.1 The signal recovery problem in orthogonal matching pursuit...... 8
2.3.2 The algorithm and solution in orthogonal matching pursuit...... 10
2.3.3 MRF matching by the orthogonal matching pursuit................ 11
2.4 Pulse sequence design............................................ 13
Chapter 3 Predict MRF mapping precision.............................. 14
3.1 Introduction..................................................... 14
3.2 Method .......................................................... 15
3.2.1 MRF randomized parameters ..................................... 15
3.2.2 Parameter matching space ...................................... 16
3.2.3 Mapping variation index........................................ 18
3.2.4 Mapping precision change under different signal acquisition numbers... 19
3.2.5 Simulate indexes of different tissues by dictionary entries.... 20
3.3 Result .......................................................... 20
3.4 Discussion ...................................................... 21
Chapter 4 Coefficient of variation for MRF mapping results .......... 23
4.1 Introduction..................................................... 23
4.2 Method .......................................................... 23
4.2.1 MR sequence ................................................... 23
4.2.2 MRF signal evolution and mapping .............................. 25
4.2.3 Simulate MRF mapping under different signal acquisition numbers 25
4.2.4 MRF mapping precision under different signal acquisition number 26
4.3 Result .......................................................... 27
4.4 Discussion ...................................................... 33
Chapter 5 Discussion and future work ................................ 37
5.1 Contour threshold selection...................................... 37
5.2 Accuracy in MR fingerprinting ................................... 39
5.3 Underestimation of the T2 value ................................. 40
References .......................................................... 42

1. Ma, D., et al., Magnetic resonance fingerprinting. Nature, 2013. 495(7440): p.187-92.
2. Cohen, O., et al., Magnetic Resonance Fingerprinting Trajectory Optimization, in Joint Annual Meeting ISMRM‐ESMRMB 2014.
3. Zhao, B., et al., Accelerated MR parameter mapping with low‐rank and sparsity constraints. Magnetic Resonance in Medicine, 2014.
4. Wang, Z., et al. MRF denoising with compressed sensing and adaptive filtering. in IEEE 11th International Symposium on Biomedical Imaging. 2014.
5. Eo, T.-j., et al., Effective data sharing method for extreme cartesian undersampling in MRF, in Joint Annual Meeting ISMRM‐ESMRMB. 2014.
6. McGivney, D.F., et al., SVD compression for magnetic resonance fingerprinting in the time domain. IEEE Trans Med Imaging, 2014. 33(12): p. 2311-22.
7. Jiang, Y., et al., MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout. Magnetic Resonance in Medicine, 2014.
8. Jiang, Y., et al., Simultaneous T1, T2, Diffusion and Proton Density Quantification with MR Fingerprinting, in Joint Annual Meeting ISMRM‐ESMRMB. 2014.
9. Christen, T., et al., MR vascular fingerprinting: A new approach to compute cerebral blood volume, mean vessel radius, and oxygenation maps in the human brain. Neuroimage, 2014. 89: p. 262-270.
10. Gao, Y., et al., Preclinical MR fingerprinting (MRF) at 7 T: effective quantitative imaging for rodent disease models. NMR in Biomedicine, 2015. 28(3): p. 384-394.
11. Schmitt, P., et al., Inversion recovery TrueFISP: quantification of T1, T2, and spin density. Magnetic resonance in medicine, 2004. 51(4): p. 661-667.
12. Bernstein, M.A., K.F. King, and X.J. Zhou, Handbook of MRI pulse sequences. 2004, Amsterdam; Boston: Academic Press.
13. Bittoun, J., J. Taquin, and M. Sauzade, A computer algorithm for the simulation of any nuclear magnetic resonance (NMR) imaging method. Magnetic Resonance Imaging, 1984. 2(2): p. 113-120.
14. Tropp, J.A. and A.C. Gilbert, Signal recovery from random measurements via orthogonal matching pursuit. Ieee Transactions on Information Theory, 2007. 53(12): p. 4655-4666.
15. Ma, D., et al., MR Fingerprinting: Rapid Simultaneous Quantification of T1, T2, Proton Density and Off‐Resonance Using a Spiral Trajectory, in ISMRM 21st Annual Meeting & Exhibition. 2013.

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