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Title: SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation

Abstract

Purpose: To develop a practical approach for accurate contour deformation when deformable image registration (DIR) is used for atlas-based segmentation or contour propagation in image-guided radiotherapy. Methods: A contour deformation approach was developed on the basis of 3D mesh operations. The 2D contours represented by a series of points in each slice were first converted to a 3D triangular mesh, which was deformed by the deformation vectors resulting from DIR. A set of parallel 2D planes then cut through the deformed 3D mesh, generating unordered points and line segments, which should be reorganized into a set of 2D contour points. It was realized that the reorganization problem was equivalent to solving the Chinese Postman Problem (CPP) by traversing a graph built from the unordered points with the least cost. Alternatively, deformation could be applied to a binary mask converted from the original contours. The deformed binary mask was then converted back into contours at the CT slice locations. We performed a qualitative comparison to validate the mesh-based approach against the image-based approach. Results: The DIR could considerably change the 3D mesh, making complicated 2D contour representations after deformation. CPP was able to effectively reorganize the points in 2D planes nomore » matter how complicated the 2D contours were. The mesh-based approach did not require a post-processing of the contour, thus accurately showing the actual deformation in DIR. The mesh-based approach could keep some fine details and resulted in smoother contours than the image-based approach did, especially for the lung structure. Image-based approach appeared to over-process contours and suffered from image resolution limits. The mesh-based approach was integrated into in-house DIR software for use in routine clinic and research. Conclusion: We developed a practical approach for accurate contour deformation. The efficiency of this approach was demonstrated in both clinic and research applications. This work was partially supported by Cancer Prevention & Research Institute of Texas (CPRIT) RP110562.« less

Authors:
; ; ;  [1]; ;  [2]
  1. MD Anderson Cancer Center, Houston, TX (United States)
  2. Scripps Proton Therapy Center, San Diego, CA (United States)
Publication Date:
OSTI Identifier:
22494123
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; COMPUTER CODES; COMPUTERIZED TOMOGRAPHY; GRAPH THEORY; IMAGE PROCESSING; IMAGES; LUNGS; NEOPLASMS; RADIOTHERAPY

Citation Formats

Yang, J, Zhang, L, Balter, P, Court, L, Zhang, Y, and Dong, L. SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation. United States: N. p., 2015. Web. doi:10.1118/1.4924195.
Yang, J, Zhang, L, Balter, P, Court, L, Zhang, Y, & Dong, L. SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation. United States. doi:10.1118/1.4924195.
Yang, J, Zhang, L, Balter, P, Court, L, Zhang, Y, and Dong, L. Mon . "SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation". United States. doi:10.1118/1.4924195.
@article{osti_22494123,
title = {SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation},
author = {Yang, J and Zhang, L and Balter, P and Court, L and Zhang, Y and Dong, L},
abstractNote = {Purpose: To develop a practical approach for accurate contour deformation when deformable image registration (DIR) is used for atlas-based segmentation or contour propagation in image-guided radiotherapy. Methods: A contour deformation approach was developed on the basis of 3D mesh operations. The 2D contours represented by a series of points in each slice were first converted to a 3D triangular mesh, which was deformed by the deformation vectors resulting from DIR. A set of parallel 2D planes then cut through the deformed 3D mesh, generating unordered points and line segments, which should be reorganized into a set of 2D contour points. It was realized that the reorganization problem was equivalent to solving the Chinese Postman Problem (CPP) by traversing a graph built from the unordered points with the least cost. Alternatively, deformation could be applied to a binary mask converted from the original contours. The deformed binary mask was then converted back into contours at the CT slice locations. We performed a qualitative comparison to validate the mesh-based approach against the image-based approach. Results: The DIR could considerably change the 3D mesh, making complicated 2D contour representations after deformation. CPP was able to effectively reorganize the points in 2D planes no matter how complicated the 2D contours were. The mesh-based approach did not require a post-processing of the contour, thus accurately showing the actual deformation in DIR. The mesh-based approach could keep some fine details and resulted in smoother contours than the image-based approach did, especially for the lung structure. Image-based approach appeared to over-process contours and suffered from image resolution limits. The mesh-based approach was integrated into in-house DIR software for use in routine clinic and research. Conclusion: We developed a practical approach for accurate contour deformation. The efficiency of this approach was demonstrated in both clinic and research applications. This work was partially supported by Cancer Prevention & Research Institute of Texas (CPRIT) RP110562.},
doi = {10.1118/1.4924195},
journal = {Medical Physics},
number = 6,
volume = 42,
place = {United States},
year = {Mon Jun 15 00:00:00 EDT 2015},
month = {Mon Jun 15 00:00:00 EDT 2015}
}