Segmentation of 3D Tubular Tree Structures in Medical Images ...

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88 Chapter 5. Liver Vascular Tree Segmentation Table 5.2: Summary of evaluation results on clinical liver CT datasets. The qualitative scores are on a scale of 1 to 3 with 1=“poor“, 2=“ok“, and 3=“good“. The ”-“ sign indicates that no vessels in these generations were visible. dataset portal vein tree hepatic vein tree segmentation quality # detected # missing # mis- # affected data # visible segmentation quality in generation data # visible branches branches connections branches quality generations 0/1 2/3 4/5 quality generations proximal medial distal d1 524 2(0.38%) 0 0 3 4 3 3 3 3 3 3 3 3 d2 210 0 0 0 2 2 3 2 - 3 3 3 3 3 d3 162 0 0 0 3 3 3 3 - 3 3 3 3 3 d4 625 0 0 0 3 5 3 3 3 3 3 3 3 3 d5 566 0 0 0 2 5 3 3 3 1 3 2 2 2 d6 224 0 1(0.45%) 3(1.34%) 3 4 3 3 3 3 3 3 3 3 d7 304 0 0 0 2 3 3 2 - 1 3 3 3 3 d8 212 3(1.40%) 0 0 2 3 3 2 - 1 3 3 3 3 d9 453 0 0 0 3 5 3 3 3 3 3 3 3 3 d10 138 0 0 0 2 4 3 3 2 1 2 3 3 - d11 117 0 0 0 3 3 3 3 - 3 3 3 3 3 d12 102 0 2(1.96%) 5(4.90%) 3 3 3 3 3 3 3 3 3 3 d13 70 0 0 0 2 2 2 2 - 1 2 3 3 - d14 380 3(0.78%) 0 0 2 4 3 3 3 2 3 3 3 3 d15 72 3(4.00%) 0 0 2 3 3 3 - 1 2 2 2 - average 277.27 0.73 0.2 0.53 (0.26%) (0.07%) (0.19%)
5.3. Evaluation and Results 89 (a) Axial cutting plane through the dataset. (b) Coronal cutting plane indicated by the white line in (a) showing anisotropy. Figure 5.6: Unsegmented vessel (arrow) found by the radiologist. (a) Segmentation result showing the hepatic artery (bright) in proximity of the portal vein (dark). (b) Cutting plane through the dataset indicated by the black line in (a), showing two hepatic arteries (1 & 2) close to the portal vein (3). (c) While artery (2) was successfully detected, artery (1) was too close to the portal vein such that no tubular structure was detected/extracted. Instead, this part of the artery was segmented as part of the portal vein. Figure 5.7: Unsuccessfully detected portal artery. parts of the vessel trees and consisted of up to 3 branches. No misconnection of larger vessels was observed. Data and segmentation quality: CT data quality and segmentation quality were assessed qualitatively by the radiologist, ranking them as “poor”, “ok”, or “good”. A summary of all scores is given in Table 5.2. For evaluation, results of several individual
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Graz University of Technology Insti
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Abstract The segmentation of tubula
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Kurzfassung Die Segmentierung tubul
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Acknowledgements I am deeply gratef
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Contents 1 Introduction 1 1.0.1 Req
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CONTENTS xv 8 Conclusion and Outloo
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xviii LIST OF FIGURES 4.2 Shape pri
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List of Tables 3.1 Average centerli
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2 Chapter 1. Introduction (a) Porta
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6 Chapter 1. Introduction (a) Inacc
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8 Chapter 1. Introduction features
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18 Chapter 2. Extraction of Tubular
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Page 60 and 61: 38 Chapter 2. Extraction of Tubular
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Page 99 and 100: Chapter 5 Liver Vascular Tree Segme
Page 101 and 102: 5.2. Method 79 (a) MIP of the datas
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Page 115 and 116: 5.4. Discussion 93 results. Selle
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Page 120 and 121: 98 Chapter 6. Coronary Artery Tree
Page 131 and 132: Chapter 7 Airway Tree Segmentation
Page 133 and 134: 7.2. Methods 111 shown in Fig. 7.1.
Page 135 and 136: 7.2. Methods 113 Additionally, the
Page 137 and 138: 7.3. Evaluation and Results 115 Gro
Page 139 and 140: 7.3. Evaluation and Results 117 Tab
Page 141 and 142: 7.4. Discussion 119 Figure 7.5: “
Page 143 and 144: 7.5. Conclusion 121 Comparison to o
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Page 147 and 148: Chapter 8 Conclusion and Outlook Co
Page 149 and 150: 8.1. Conclusion 127 arteries - info
Page 151: 8.2. Directions for Future Work 129
Page 154 and 155: 132 Chapter A. List of Publications
Page 157 and 158: BIBLIOGRAPHY 135 Bibliography [1] A
Page 159 and 160: BIBLIOGRAPHY 137 [21] Choyke, P., Y
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BIBLIOGRAPHY 139 [41] Florin, C., P
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BIBLIOGRAPHY 141 [63] Kitslaar, P.
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BIBLIOGRAPHY 143 [85] Lindeberg, T.
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BIBLIOGRAPHY 145 [108] O’Donnell,
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BIBLIOGRAPHY 147 [129] Schmugge, S.
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BIBLIOGRAPHY 149 [150] van Bemmel,
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BIBLIOGRAPHY 151 [171] Yi, J. and R
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