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Proceedings Paper

Bladder wall flattening with conformal mapping for MR cystography
Author(s): Ruirui Jiang; Hongbin Zhu; Wei Zeng; Xiaokang Yu; Yi Fan; Xianfeng Gu; Zhengrong Liang
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Paper Abstract

Magnetic resonance visual cystoscopy or MR cystography (MRC) is an emerging tool for bladder tumor detection, where three-dimensional (3D) endoscopic views on the inner bladder surface are being investigated by researchers. In this paper, we further investigate an innovative strategy of visualizing the inner surface by flattening the 3D surface into a 2D display, where conformal mapping, a mathematically-proved algorithm with shape preserving, is used. The original morphological, textural and even geometric information can be visualized in the flattened 2D image. Therefore, radiologists do not have to manually control the view point and angle to locate the possible abnormalities like what they do in the 3D endoscopic views. Once an abnormality is detected on the 2D flattened image, its locations in the original MR slice images and in the 3D endoscopic views can be retrieved since the conformal mapping is an invertible transformation. In such a manner, the reading time needed by a radiologist can be expected to be reduced. In addition to the surface information, the bladder wall thickness can be visualized with encoded colors on the flattened image. Both normal volunteer and patient studies were performed to test the reconstruction of 3D surface, the conformal flattening, and the visualization of the color-coded flattened image. A bladder tumor of 3 cm size is so obvious on the 2D flattened image such that it can be perceived only at the first sight. The patient dataset shows a noticeable difference on the wall thickness distribution than that of the volunteer's dataset.

Paper Details

Date Published: 23 February 2010
PDF: 9 pages
Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 76250E (23 February 2010); doi: 10.1117/12.844462
Show Author Affiliations
Ruirui Jiang, Stony Brook Univ. (United States)
Hongbin Zhu, Stony Brook Univ. (United States)
Wei Zeng, Stony Brook Univ. (United States)
Xiaokang Yu, Stony Brook Univ. (United States)
Yi Fan, Stony Brook Univ. (United States)
Xianfeng Gu, Stony Brook Univ. (United States)
Zhengrong Liang, Stony Brook Univ. (United States)


Published in SPIE Proceedings Vol. 7625:
Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; Michael I. Miga, Editor(s)

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