| BIOLOGICAL SCIENCE AND ENGINEERING |
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Segmentation strategy for enhanced MR cystography based on graph theory |
| DUAN Chaijie1,2, ZHANG Yijia1,2, GUO Hui1,2, YE Datian1,2, LIANG Zhengrong3 |
1. Shenzhen Key Laboratory for Nondestructive and Minimal Invasive Medical Technology, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China;
2. Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China;
3. Stony Brook University, Stony Brook NY 11794, USA |
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Abstract Fast magnetic resonance (MR) bladder scans with artifacts and low signal to noise ratios (SNR) are used to precisely segment and achieve the bladder wall. The short scans are registered to a selected reference using an affine transformation followed by a hierarchical B-spline registration. The average of the registration results is the motion-corrected image. The graph cut method based on a closed-set model is then used segment the bladder MR image. The strategy is evaluated using both computer-generated images and clinical MR images. The results show that the average motion-corrected image with a high SNR (i.e., 3.26 for the simulated images and 2.17 for the clinical images) and less artifacts followed by a graph-cut segmentation tends to have a more accurate result. This strategy reduces the artifacts and improves the SNR to provide high resolution segmentation of the bladder wall.
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| Keywords
cystography
magnetic resonance(MR)
registration
graph cut
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Issue Date: 15 June 2015
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| [1] |
段侪杰, 田珍, 梁正荣, 等. 基于医学影像的虚拟膀胱镜技术 [J]. 中国医学物理学杂志, 2010, 27(2): 1712-1715.DUAN Chaijie, TIAN Zhen, LIANG Zhengrong, et al. A review on virtual cystoscopy techniques [J]. Chinese Journal of Medical Physics, 2010, 27(2):1712-1715. (in Chinese)
|
| [2] |
Jaume S, Ferrant M, Macq B, et al. Tumor detection in the bladder wall with a measurement of abnormal thickness in CT scans [J]. IEEE Transactions on Bio-medical Engineering, 2003, 50(3): 383-390.
|
| [3] |
LIN Qin, LIANG Zhengrong, DUAN Chaijie, et al. Motion correction for MR cystography by an image processing approach [J]. IEEE Transactions on Biomedical Engineering, 2013, 60(9): 2401-2410.
|
| [4] |
Boykov Y, Veksler O, Zabih R. Fast approximate energy minimization via graph cuts [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(11): 1222-1239.
|
| [5] |
Osher S, Sethian J A. Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulation [J]. Journal of Computational Physics, 1988, 79(1): 12-49.
|
| [6] |
LI Kang, WU Xiaodong, CHEN Ziyi, et al. Optimal surface segmentation in volumetric images—A graph-theoretic approach [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(1): 119-134.
|
| [7] |
Hochbaum D. A new-old algorithm for minimum-cut and maximum-flow in closure graphs [J]. Networks, 2001, 37(4): 171-193.
|
| [8] |
Boykov Y, Kolmogorov V. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(9): 1124-1137.
|
| [9] |
ZHANG Yijia, DUAN Chanjie, YE Datian, et al. The segmentation of MR bladder wall in 3D based on minimum closed set model [C]//2013 IEEE International Conference on Medical Imaging Physics and Engineering. Shenyang, China: IEEE, 2013: 319-323.
|
| [10] |
Henkelman R. Measurement of signal intensities in the presence of noise in MR images [J]. Medical Physics, 1985, 12(2): 232-233.
|
| [11] |
Kaufman L, Kramer D, Crooks L, et al. Measuring signal-to-noise ratios in MR imaging [J]. Radiology, 1989, 173(1): 265-267
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2015,
Vol. 55
