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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15847完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 曹建和 | |
| dc.contributor.author | Sheng-Kai Tsao | en |
| dc.contributor.author | 曹勝凱 | zh_TW |
| dc.date.accessioned | 2021-06-07T17:53:31Z | - |
| dc.date.copyright | 2012-08-19 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-18 | |
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[32]Sheng-Kai Tsao and Jenho Tsao, “A Consistent Tissue Attenuation Coefficient Estimator Using Bubble Harmonic Echoes,” IEEE Transactions on Ultrasonics. Ferroelectrics. And Frequency Control., Vol. 57, No. 12, pp. 2654-2661, 2010 [33]Hairong Shi, Tomy Varghese, Carol C. Mitchell, Matthew McCormick, Robert J. Dempsey, Marl A. Kliewer, “In vivo attenuation and equivalent scatterer size parameters for atherosclerotic carotid plaque: Preliminary results,” Ultrasonics, vol.49, pp779-785,2009 [34]L.S. Wilson, M.L. Neale, H.E. Talhami, M. Appleberg, “Preliminary results from attenuation-slpoe mapping of plaque using intravascular ultrasound” Ultrasound Med. Biol., vol. 20, pp.529-542, 1994 [35]Chung-Yuo Wu, “ An ultrasonic microbubble low-frequency imaging technique” PhD thesis, Graduate Institute of Electrical Engineering, National Taiwan University, 2004 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15847 | - |
| dc.description.abstract | 對於不同軟組織所對應的超音波特性可以被組織衰減係數α所定量的表示。傳統上，我們利用組織背散射訊號估計α，其可被歸類為一種空間平均的方法。在本文中我們提出一個利用被組織衰減後的微氣泡訊號估計α的方式。不同於以往空間平均新的方法用時間平均完成。主要的優點為時間平均的方法可以取得大量的估計樣本。首先，我們利用Kuc以及Miller的結果提出一個經過組織衰減的氣泡回波模型。利用此模型我們開發一個α的估計子。估計偏差可能會因為非理想的氣泡反應、低訊雜比以及兩血管中微氣泡分佈的不對稱所產生。另一個估計問題為估計時間與精確度的關係。一個提高效率的方式為引進頻率分集的技術增加估計樣本的數量，針對此技術我們提出一個使用最大概似法的估計子。頻率分集的技術也被應用於補償兩血管中微氣泡分佈的不對稱所產生的估計偏差。在實驗驗證方面，我們應用一個簡單的仿體驗證使用氣泡的一次與二次諧振訊號皆可得到足夠精確的估計。然而利用一次諧振訊號會被組織序號干擾而產生偏差的估計。我們也證明頻率分集確實可增進估計效率以及估計的偏差值確實會受到訊雜比所影響。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-07T17:53:31Z (GMT). No. of bitstreams: 1 ntu-101-D93942021-1.pdf: 1223926 bytes, checksum: 7ea416db46ce28a8f14eccb6c5243547 (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 1.INTRODUCTION.......................................... 1
2. TAC ESTIMATION TECHNIQUES............................ 7 2.1.TAC estimator using tissue backscattering signal........................................... 8 2.1.1Frequency domain estimator................... 9 2.1.2Time domain estimator........................ 10 2.1.3Video signal analysis........................ 12 2.2. Application of TAC.............................. 13 3. BUBBLE PROPERTIES AND PERFUSION...................... 15 3.1. Analytical solutions of RPNNP equation using two- frequency excitation signal..................... 17 3.2. Cardiac contrast perfusion technique........... 22 4. A CONSISTENT TAC ESTIMATOR USING BUBBLE HARMONIC ECHOES............................................... 25 4.1. Signal models of attenuated contrast fundamental and second harmonic echoes...................... 26 4.1.1 Signal model of attenuated single bubble echo ...................................... 26 4.1.2 Stochastic process of attenuated bubble echo signal..................................... 29 4.2. TAC estimation environment...................... 33 4.3. Consistent TAC estimator........................ 36 5. FREQUENCY DIVERSITY TECHNIQUE........................ 41 5.1. Diversity strategy.............................. 42 5.2. Frequency spacing selection and Independency of diversity signals............................... 45 5.2.1 Frequency spacing selection............... 46 5.2.2 Independency of diversity signals......... 47 5.3. Diversity Method............................... 50 5.3.1 The ML combiner........................... 52 5.3.2 Diversity gain............................ 54 6. BIAS CONSIDERATION................................... 57 6.1. Bias caused by non-ideal bubble harmonic property....................................... 58 6.2. Bias caused by additive Gaussian noise......... 60 6.2.1 modified bubble harmonic model............ 61 6.3. Bias caused by different bubble number distribution of two vessels.................... 64 6.3.1 Signal model with varying bubble number................................... 66 6.3.2 Unbiased TAC estimator based on harmonic ratio.................................... 69 6.4. Bias and efficiency consideration............. 72 7. EXERIMENT VERIFICATION .............................. 75 7.1. TAC estimation using single-band bubble echo.. 76 7.1.1 Experimental setup....................... 76 7.1.2 Estimation using bubble fundamental and second harmonic.......................... 80 7.1.3 Noise caused bias....................... 87 7.2 TAC estimation using frequency diversity technique..................................... 91 7.2.1 Experimental setup....................... 91 7.2.2 Different diversity combiner............. 92 8. CONCLUSIONS.......................................... 103 REFERENCES............................................. 105 PUBLICATION LIST....................................... 111 | |
| dc.language.iso | en | |
| dc.subject | 時間平均 | zh_TW |
| dc.subject | 組織衰減係數 | zh_TW |
| dc.subject | 微氣泡諧振 | zh_TW |
| dc.subject | 頻率分集 | zh_TW |
| dc.subject | 非線性訊號 | zh_TW |
| dc.title | 一個使用氣泡諧波訊號估測組織衰減係數的技術 | zh_TW |
| dc.title | A tissue attenuation coefficient estimation technique using bubble harmonic signals | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 葉秩光,陳文翔,林文澧,羅孟宗 | |
| dc.subject.keyword | 組織衰減係數,微氣泡諧振,頻率分集,非線性訊號,時間平均, | zh_TW |
| dc.subject.keyword | tissue attenuation coefficient,bubble harmonic,frequency diversity,nonlinear signal,time averaging, | en |
| dc.relation.page | 112 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2012-08-18 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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