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研究生:鄭文堯
研究生(外文):Wen-Yao Cheng
論文名稱:基於互資訊下使用Z軸位移調整的CT與PET腦部影像校準
論文名稱(外文):A Study on CT and PET Brain Image Co-registration Based on Mutual Information Using Z-axis Shifting Alignment
指導教授:駱榮欽駱榮欽引用關係
指導教授(外文):Rong-Chin Lo
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電腦通訊與控制研究所
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:2003
畢業學年度:91
語文別:英文
論文頁數:71
中文關鍵詞:正子放射斷層攝影電腦斷層攝影解剖性結構性功能性影像校準
外文關鍵詞:PETCTMutual InformationAnatomicalFunctionalRegistrationCo-registration
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醫學影像依成像的原理的不同,有磁振造影 (MRI)、電腦斷層造影(CT)、正子斷層造影 (PET) 和功能性磁振造影 (fMRI)等,根據其成像的方式又可以區分為解剖性(Anatomical) 及功能性(Functional)這兩大類。所謂解剖性影像是指取得的影像能夠清楚的顯示及辨別器官或組織的輪廓及外形,磁振造影及電腦斷層造影即屬於此類;而功能性影像是指能夠獲的組織或器官的新陳代謝情形,正子斷層造影和功能性磁振造影即屬於此類。
結合功能性及解剖性影像能夠提供診療者更多的資訊,以利於疾病的診斷及治療。雖然已經有結合電腦斷層造影及正子斷層造影的機器問世(PET/CT Scanner),但由於其價格昂貴,目前使用的醫療院所仍然有限。
對於功能性及解剖性影像,我們可藉由電腦影像處理的方式來結合在一起,稱為影像校準(Co-registration)。也由於電腦技術進步的快速,使的電腦的運算速度越快功能越強大但成本卻越來越便宜。
經由影像處理的方式來達到兩者影像校準的目的可以讓沒有PET/CT Scanner 的醫療單位,仍能將兩組不同種類的影像結合成一組影像,以提供診療者更多的資訊,並且能夠以更經濟的方式來完成影像校準。
在論文中我們提出新的校準方法,其中包括三部份,(1) 利用腦部的對稱性來將歪斜的影像調整到正中央的位置。(2) 利用三個仿射不變性的參數以及 DICOM 的資訊來調整 Z 軸方向的偏移。(3) 利用互資訊的原理來對最後的結果作一個更精確的調整。經過實例測試之後,影像校準的結果,其誤差值均在可接受範圍,這個結論是讓人滿意的,同時我們建立了一套具有人機介面的醫學影像處理與校準系統。
In clinical diagnosis, different modalities usually provide complementary information. For example, CT(computed tomography) images provide anatomical information of human body in radiotherapy. PET (positron emission tomography) image provide the activity of metabolism of organs, which helps clinician to realize the biochemistry and physiology of the human body.
Although several medical centers own “PET/CT Scanner” equipment, but the price of the equipment is so expensive, they only can use CT or PET Scanner to acquire the images and register them by image processing.
Due to the PET image being functional but low-resolution, to segment the geometrical feature from the images is difficult, and the co-registration process might be failure.
Using Mutual Information (MI) of PET and CT images to register both images, clinicians can get more information on the focal part. The multi-modality registration of processing provides more information than single-modality.
But the computing time to find the maximization of MI is expansive and the process may fall into a local maximum. To improve the drawback of MI, in the study, we propose an improved algorithm shown as Figure 1. First, we use ideal Mid-Sagittal Plane (iMSP) Algorithm and Z-axis shifting Alignment to align CT and PET images to coincide the center positions of two corresponding image slices of the same organ in rough. Second, we calculate MI of the different image slices, to find the maximum MI as aligned exactly. Finally, a co-registration system with window-based interface built by Borland C++ Builder is introduced. And, several experimental results of iMSP, Z-shifting alignment, and Mutual Information criteria, are included to demonstrate the applicability of the proposed methods.
ABSTRACT IN CHINESE...iii
ABSTRACT IN ENGLISH...v
ACKNOWLEDGMENTS...vii
CONTENTS...viii
LIST OF FIGURES...x
LIST OF TABLES...xii
Chapter 1 INTRODUCTION...1
1.1 Research Motivation..1
1.2 Research and Survey...3
1.2.1 Survey of Medical Image Registration...3
1.2.2 Survey of ideal Mid-Sagittal Plane Algorithm...4
1.2.3 Survey of Mutual Information...5
1.3 Thesis Organization...5
Chapter 2 INTRODUCTION TO COMPUTED TOMOGRAPHY AND POSITRON EMISSION TOMOGRAPHY IMAGING...6
2.1 Physical Foundation of CT...6
2.1.1 Fundamentals of X-ray...6
2.1.2 Conventional X-ray Radiography...9
2.1.3 Computed Tomography...9
2.2 Physical Foundation of PET...13
2.2.1 The Properties of PET Images...14
Chapter 3 PROPOSED PET AND CT IMAGE CO-REGISTRATION METHODS...17
3.1 ideal Mid-Sagittal Plane Algorithm...17
3.2 Z-axis Shifting Alignment Process...25
3.2.1 Experimental Results of Z-Shifting Alignment Process...27
3.3 Mutual Information Criterion...31
3.3.1 The Theory of Mutual Information...33
3.3.2 Experimental results of Mutual Information...37
Chapter 4 THE MEDICAL IMAGE CO-REGISTRATION SYSTEM...42
4.1 The Useful DICOM Information in The Study 42
4.1.1 The Brief Explanation of DICOM Standard 43
4.1.2 The Header Description of the DICOM Image Files...44
4.2 Image Processing Techniques...49
4.3 The Presentation of the Registered Image...51
4.3.1 Pseudo Color Presentation...51
4.3.2 Image Compositing Based on Transparency Model...52
4.4 The PET-CT Co-registration System...56
Chapter 5 CONCLUSIONS AND FUTURE WORK...61
5.1 Conclusions...61
5.1.1 ideal Mid-Sagittal Plane Algorithm ...61
5.1.2 Z-axis Shifting Alignment...62
5.1.3 Mutual Information Criterion...63
5.2 FUTURE WORKS...63
5.2.1 Improving Accuracy of Image Transformation...63
5.2.2 Expanding Capability of the System...64
REFERENCES...66
VITA...70
PUBLICATION LIST OF WEN-YAO CHENG...71
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