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Proceedings Paper

Segmentation of multispectral bladder MR images with inhomogeneity correction for virtual cystoscopy
Author(s): Lihong Li; Zhengrong Liang; Su Wang; Hongyu Lu; Xinzhou Wei; Mark Wagshul; Marlene Zawin; Erica J. Posniak; Christopher S. Lee
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Paper Abstract

Virtual cystoscopy (VC) is a developing noninvasive, safe, and low-cost technique for bladder cancer screening. Multispectral (T1- and T2-weighted) magnetic resonance (MR) images provide a better tissue contrast between bladder wall and bladder lumen comparing with computed tomography (CT) images. The intrinsic T1 and T2 contrast of the urine against the bladder wall eliminates the invasive air insufflation procedure which is often used in CT-based VC. We propose a new partial volume (PV) segmentation scheme with inhomogeneity correction to segment multispectral MR images for tumor screening by virtual cystoscopy. The proposed PV segmentation algorithm automatically estimates the bias field and segments tissue mixtures inside each voxel of MR images, thus preserving texture information. Experimental results indicate that the present scheme is promising towards mass screening by virtual cystoscopy means.

Paper Details

Date Published: 12 March 2008
PDF: 5 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 69160U (12 March 2008); doi: 10.1117/12.769914
Show Author Affiliations
Lihong Li, CUNY (United States)
SUNY (United States)
Zhengrong Liang, SUNY (United States)
Su Wang, SUNY (United States)
Hongyu Lu, SUNY (United States)
Xinzhou Wei, New York City College of Technology (United States)
Mark Wagshul, SUNY (United States)
Marlene Zawin, SUNY (United States)
Erica J. Posniak, SUNY (United States)
Christopher S. Lee, SUNY (United States)


Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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