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研究生:胡育彰
研究生(外文):Yu-Chang Hu
論文名稱:動態影像估測之醫學影像應用
論文名稱(外文):Image Motion Estimation for Medical Image Applications
指導教授:林康平林康平引用關係
指導教授(外文):Kang-Ping Lin
學位類別:碩士
校院名稱:中原大學
系所名稱:電機工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:英文
論文頁數:76
中文關鍵詞:動態估測光流法左心室體積量測
外文關鍵詞:perfusionvolume measurementmotion estimationbreath holding
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  • 被引用被引用:3
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在醫學影像處理中,心臟的運動量測是一個熱門且極為重要的研究領域,它能夠幫助醫生正確的診斷心臟方面的疾病。一般而言,對於心臟的運動估測與做左心室體積大小的量測,大部分都是建立在X-ray (X-光) 和MRI (核磁共振影像) 的影像上,因此,一個擁有可靠與強大量測技術的方法,對於疾病的診斷有很大的幫助。所以,本論文研究的目的,是在於處理Perfusion影像的位移修正,與左心室體積大小的量測。
心臟的Perfusion影像,通常是建立在一個隨時間變化的機制上,並以數位的方式顯示左心室和右心室在注射藥劑後於一連續時間上的變化。而由此一連續時間上的影像灰階變化,對於臨床疾病得診斷上是非常有幫助的。這是因為藉由左心室與心肌壁上的影像灰階變化,可以反應出血液的流速與濃度,在臨床上這是一個診斷心臟功能的一個有用資訊。 在影像的擷取過程中,為了保持影像的穩定性,通常都會要求病人停止呼吸,避免心臟因呼吸的影響,導致胸腔擴張使得心臟發生偏移,但由於一般病人本身即具有心臟方面的疾病,因此不易控制呼吸的停止,使得在做定量分析時容易出現錯誤,因此須對其加以修正。在本研究中將利用光流法與區塊比對法估測特定的特徵點,加以修正其偏移量。
另一個研究的目的,在於量測左心室體積的大小。一般對於心室體積的量測,大都使用影像分割法,而大部分的分割法皆能得到理想的影像分割結果。但是此一方法卻容易將心肌壁所突出到心室的部份分隔開來,造成量測的誤差性。在本研究中,我們希望利用動態追蹤的技術,經由特定之特徵點的運動以及補點方法的利用,期能減低量測時的誤差,並加速量測時所需的時間。
最後,本文的最終目的在於希望能提供另一個處理動態修正與心室體積量測的方法, 並將其實用於一般之臨床診斷系統中。
In medical image process, cardiac motion estimation is a popular and important research for physicians to diagnose cardiac disease. There are many researches for cardiac motion estimation and left ventricle volume measurement based on X-ray films, MRI images, etc. Therefore, a reasonable and powerful technology will be useful for disease diagnosis. So, the goal of this study is to deal with perfusion images for motion correction of cardiac images and volume measurement of left ventricle.
Generally, cardiac perfusion images are based on time parameter extraction and display from a digitized cardiac image series following contrast injection into the left ventricle and right ventricle. Extraction of time parameters from pixel-densograms is a very useful and clinically relevant procedure. This is particularly true when applied to the left ventricle and myocardial, since time parameters indicate the progress of the contract bolus, which in turn reflects the speed and quantify of blood flow. But breath holding is the problem of perfusion images obtained. When patients don’t hold their breath well, it would make the heart moving away from fixed position. It would make us confused by the radioactive medicament concentration for diagnosing. In this study, we will use a tracking process to fix the left ventricle into the same position. Optical flow estimation and block match are two of the most used motion estimation methods. They will be compared how the accuracy they are when we deal with motion correction for perfusion images.
Another study is to measure the volume value of left ventricle. A most used technology for volume measurement of left ventricle is segmentation method. Any kinds of segmentation method would have a good results for segmenting to left ventricle and myocardial, but the common problem for left ventricle volume measurement is excluding pop-muscle of left ventricle for measuring. In this study, we use a tracking method to locate the landmarks in all frames of left ventricle volume and use an interpolation process to link landmarks for left ventricle volume measurement. It could solve the problem of excluding pop-muscle and decrease the error measurement of left ventricle volume. As this process applying, it also can decrease the computing time for volume measurement.
After all, our purpose of this study is to provide another procedure for motion correction and volume measurement of left ventricle.
第一章 簡介
1-1背景.................................................1-1
1-2動機.................................................1-2
1-3全文架構.............................................1-4
第二章 動態估測
2-1動態估測.............................................2-2
2-2光流法 ..............................................2-4
2.2.1光流法...............................................2-5
2.2.2Horn 和 Schunck 法...................................2-7
2.2.3修正光流法...........................................2-9
2-3區塊比對法..........................................2-11
2-3-1區塊比對法..........................................2-11
2-3-2匹配準則............................................2-12
2-4估測之結果..........................................2-13
第三章 Perfusion 影像之運用
3-1Perfusion 影像 ......................................3-1
3-2動態位移修正.........................................3-3
3-3左心室特徵點之運動量測...............................3-6
3-4動態追蹤之使用界面...................................3-8
3-5動態位移修正之評估..................................3-10
3-6動態位移修正之結果..................................3-11
第四章TureFIPS影像之運用
4-1TureFIPS 影像........................................4-1
4-2TureFIPS 影像之體積量測..............................4-3
4-3左心室特徵點之追蹤與體積量測.........................4-7
4-4補差之於左心室體積量測..............................4-10
4-5左心室體積量測之結果................................4-12
第五章 結論
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Gatehouse, Kim Rajappan, Jennifer Keegan, David N. Firmin, Dudley J. Pennell, “Left Ventricular Quantification in Heart Failure by Cardiovascular MR Using Prospective Respiratory Navigation Gating: Comparison With Breath-Hold Acquisition”, JOURNAL OF MAGNETIC RESONANCE IMAGING 11: 411-417, 2000[20]Martin J. Graves, Elizabeth Berry, Armen Avedisijan B Eng, Martin Westhead, Richard T. Block, David J. Beacock, Steven Kelly, Pekka Niemi, “A Multicenter Validation of an Active Contour-Based left Ventricular Analysis Technique”, JOURNAL OF MAGNETIC RESONANCE IMAGING 12: 232-239, 2000[21]Joosh P.A. Kuijer, J. Tim Marcus, Marco J.W. Gott, Albert C.Van Rossum, Robert M. Heethaar,” Simultaneous MRI Tagging and Through-Plane Velocity Quantification: A Three-Dimensional Myocardial Motion Tracking Algorithm”, JOURNAL OF MAGNETIC RESONANCE IMAGING 9: 409-419, 1999[22]Fan, C.M.; Namazi, N.M.,”Image motion estimation from blurred and noisy image sequences”, Image Processing, 1998. ICIP 98. 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