Master's Thesis - Studierstube Augmented Reality Project - Graz ...

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CONTENTS A Intermediate File Format Definition 133 A.1 Master File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 A.2 Data Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 B UML Class Diagrams In Detail 140 Glossary 146 List of Figures 151 List of Tables 154 References 167 vii
Chapter 1 Introduction Assessment of blood flow properties is crucial in the understanding and diagnosis of many cardiovascular diseases. The Magnetic Resonance (MR) through-plane phase contrast method provides a lot of useful information from flow through cross sections or velocities in preferred directions. However, its usefulness in situations involving complex fluid dynamics - as for example in the cardiac chambers - is limited, because the main directions of flow are neither known nor constant in time. Conceptually the easiest way to acquire three-dimensional blood flow data is to measure both throughplane and in-plane velocity components via phase contrast sequences. Velocity vectors are determined on each imaging plane: In the case of the combined through-plane and in-plane measurement for each pixel. This measurement method is already available [Reiter2006; ClincalMRI2006], but the vast amount of data and its complex composition requires the development of tools and methods for a clear representation aimed at physicians who may evaluate possible vascular diseases or understand the human cardiovascular system in a better way. Highperformance real time GPU accelerated visualization techniques help to investigate the resulting four-dimensional datasets in this work. These methods are also applicable to other kinds of flow data. The problem we are dealing with is that radiologists and physicians can form mental images of a certain structure from human anatomical images slices, but flow information given in additional images is not perceptible in a similar way. The main problem with flow sensitive sequences is that three dimensional flow data requires three additional images for each measured slice image and that they have to be investigated in addition to basic morphological data. For physicians this is not feasible. Flow is also changing 1
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3.4 Image Contrast (a) T1-contrast
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3.5 Cine Cardiac Fast Low-Angle Sho
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4.1 Requirements visualization of c
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4.2 Data Preprocessing 4.2 Data Pre
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4.3 Intermediate File Format a simp
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4.4 Visualization Framework impleme
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4.4 Visualization Framework Figure
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Chapter 5 Implementation This chapt
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5.2 iMEDgine extensions Figure 5.1:
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5.2 iMEDgine extensions which eases
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5.2 iMEDgine extensions solution fu
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5.2 iMEDgine extensions 23 cam_posi
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5.2 iMEDgine extensions Figure 5.4:
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5.2 iMEDgine extensions • SoSFStr
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5.2 iMEDgine extensions 6 Z=" -238.
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5.3 Visualization nodes and subgrap
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Chapter 6 Experiments Several atten
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6.3 Results 6.3 Results To complete
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6.4 Scalability activity. The highe
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6.4 Scalability (a) Stream lines fo
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6.4 Scalability (a) Stream tubes ap
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6.4 Scalability Figure 6.10: Compar
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Chapter 7 Future Work This chapter
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7.3 Derived Magnitudes possibilitie
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7.5 Clinical Evaluations (a) Stereo
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Beside the improvement of known spa
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Appendix A Intermediate File Format
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A.2 Data Files Offset Name Type Des
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This chapter supplements chapter 5
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143 Figure B.3: An thinned out UML
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Figure B.5: This UML class diagram
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Glossary Notation bipolar gradient
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Glossary Notation Description MIP M
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Glossary Notation Description shade
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LIST OF FIGURES 3.5 The slice-profi
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List of Tables 2.1 CPU - GPU analog
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REFERENCES [Brill1994] M. Brill, W.
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REFERENCES [iMedgine2006] T. Gross,
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REFERENCES [Kniss2002a] Joe Kniss,
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REFERENCES [Markl2003] Michael Mark
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REFERENCES [Roth1982] Scott D. Roth
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REFERENCES [Vivek1999] andAlexPang
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INDEX flow data, 135 format definit
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Master's Thesis - Studierstube Augmented Reality Project - Graz ...

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