The first important step in pre-processing data for 3D virtual colonoscopy requires careful segmentation of a complicated shaped colon. We describe an automatic colon segmentation method with a new patient-friendly bowel preparation scheme. This new bowel preparation makes the segmentation more appropriate for digitally removing undesirable remains in the colon. With the aim of segmenting the colon accurately, we propose two techniques which can solve the partial-volume-effect (PVE) problem on the boundaries between low and high intensity regions. Based on the features of the adverse PVE voxels on the gas and fluid boundary inside the colon, our vertical filter eliminates these PVE voxels. By seriously considering the PVE on the colon boundary, our gradient-magnitude-based region growing algorithm improves the accuracy of the boundary. The result of the automatic colon segmentation method is illustrated with both extracted 2D images from the experimental volumetric abdominal CT datasets and a reconstructed 3D colon model.
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Mie SATO, Sarang LAKARE, Ming WAN, Arie KAUFMAN, Zhengrong LIANG, Mark WAX, "An Automatic Colon Segmentation for 3D Virtual Colonoscopy" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 1, pp. 201-208, January 2001, doi: .
Abstract: The first important step in pre-processing data for 3D virtual colonoscopy requires careful segmentation of a complicated shaped colon. We describe an automatic colon segmentation method with a new patient-friendly bowel preparation scheme. This new bowel preparation makes the segmentation more appropriate for digitally removing undesirable remains in the colon. With the aim of segmenting the colon accurately, we propose two techniques which can solve the partial-volume-effect (PVE) problem on the boundaries between low and high intensity regions. Based on the features of the adverse PVE voxels on the gas and fluid boundary inside the colon, our vertical filter eliminates these PVE voxels. By seriously considering the PVE on the colon boundary, our gradient-magnitude-based region growing algorithm improves the accuracy of the boundary. The result of the automatic colon segmentation method is illustrated with both extracted 2D images from the experimental volumetric abdominal CT datasets and a reconstructed 3D colon model.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_1_201/_p
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@ARTICLE{e84-d_1_201,
author={Mie SATO, Sarang LAKARE, Ming WAN, Arie KAUFMAN, Zhengrong LIANG, Mark WAX, },
journal={IEICE TRANSACTIONS on Information},
title={An Automatic Colon Segmentation for 3D Virtual Colonoscopy},
year={2001},
volume={E84-D},
number={1},
pages={201-208},
abstract={The first important step in pre-processing data for 3D virtual colonoscopy requires careful segmentation of a complicated shaped colon. We describe an automatic colon segmentation method with a new patient-friendly bowel preparation scheme. This new bowel preparation makes the segmentation more appropriate for digitally removing undesirable remains in the colon. With the aim of segmenting the colon accurately, we propose two techniques which can solve the partial-volume-effect (PVE) problem on the boundaries between low and high intensity regions. Based on the features of the adverse PVE voxels on the gas and fluid boundary inside the colon, our vertical filter eliminates these PVE voxels. By seriously considering the PVE on the colon boundary, our gradient-magnitude-based region growing algorithm improves the accuracy of the boundary. The result of the automatic colon segmentation method is illustrated with both extracted 2D images from the experimental volumetric abdominal CT datasets and a reconstructed 3D colon model.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - An Automatic Colon Segmentation for 3D Virtual Colonoscopy
T2 - IEICE TRANSACTIONS on Information
SP - 201
EP - 208
AU - Mie SATO
AU - Sarang LAKARE
AU - Ming WAN
AU - Arie KAUFMAN
AU - Zhengrong LIANG
AU - Mark WAX
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2001
AB - The first important step in pre-processing data for 3D virtual colonoscopy requires careful segmentation of a complicated shaped colon. We describe an automatic colon segmentation method with a new patient-friendly bowel preparation scheme. This new bowel preparation makes the segmentation more appropriate for digitally removing undesirable remains in the colon. With the aim of segmenting the colon accurately, we propose two techniques which can solve the partial-volume-effect (PVE) problem on the boundaries between low and high intensity regions. Based on the features of the adverse PVE voxels on the gas and fluid boundary inside the colon, our vertical filter eliminates these PVE voxels. By seriously considering the PVE on the colon boundary, our gradient-magnitude-based region growing algorithm improves the accuracy of the boundary. The result of the automatic colon segmentation method is illustrated with both extracted 2D images from the experimental volumetric abdominal CT datasets and a reconstructed 3D colon model.
ER -