Paper
13 March 2006 Fast and accurate tract unfolding based on stable volumetric image deformation
Author Affiliations +
Abstract
This paper presents an improved method for virtually unfolding an organ and visualizing its entire luminal surface in only one view. Unfolded tract views can be very useful as they allow doctors to understand various kinds of information of the luminal surface intuitively, just like observing a pathological specimen. However, the previous method cannot correctly reproduce the luminal surface because elasticity for the organ walls is quite coarse defined. Thus, three improvements are proposed: (1) accurate elastic modeling using mass points and Kelvin-Voigt visco-elastic elements, (2) stable image deformation by the Newmark-β method, and (3) automatically directing organ walls to flat shapes by forces determined from their surface normals. Unfolded views generated by the proposed method from seventeen 3D CT image datasets are compared with those by the previous method, virtual endoscopic images, and pathological specimens. Several regions on the luminal surface, which could not be reproduced by the previous method, were accurately reproduced. Bending and concave parts of organ walls, which were difficult to unfold in the previous method, were satisfactorily flattened by introducing improved deformation processes. Computation time was reasonably reduced. Unfolded views of twelve cases were presented to doctors for surgical planning. The unfolded views generated by the proposed method were considered to have well reproduced all lesions as well as fold patterns observed in virtual endoscopic images.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
TrungDung Truong, Takayuki Kitasaka, Kensaku Mori, and Yasuhito Suenaga "Fast and accurate tract unfolding based on stable volumetric image deformation", Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 614317 (13 March 2006); https://doi.org/10.1117/12.652927
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Cited by 2 scholarly publications and 1 patent.
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KEYWORDS
Stomach

Natural surfaces

Data modeling

Computed tomography

Visualization

Image visualization

Colon

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