Contour propagation using non-uniform cubic B-splines for lung tumor delineation in 4D-CT

  • Yongchuan Liu
  • Renchao Jin
  • Mi Chen
  • Enmin Song
  • Xiangyang Xu
  • Sheng Zhang
  • Chih-Cheng Hung
Original Article

Abstract

Purpose

Accurate target delineation is a critical step in radiotherapy. In this study, a robust contour propagation method is proposed to help physicians delineate lung tumors in four-dimensional computer tomography (4D-CT) images efficiently and accurately.

Methods

The proposed method starts with manually delineated contours on the reference phase. Each contour is fitted by a non-uniform cubic B-spline curve, and its deformation on the target phase is achieved by moving its control vertexes such that the intensity similarity between the two contours is maximized. Since contour is usually the boundary of lesion or tissue which may deform quite differently from the tissues outside the boundary, the proposed method treats each contour as a deformable entity, a non-uniform cubic B-spline curve, and focuses on the registration of contour entity instead of the entire image to avoid the deformation of contour to be smoothed by its surrounding tissues, meanwhile to greatly reduce the time consumption while keeping the accuracy of the contour propagation. Eighteen 4D-CT cases with 444 gross tumor volume (GTV) contours manually delineated slice by slice on the maximal inhale and exhale phases are used to verify the proposed method.

Results

The Jaccard similarity coefficient (JSC) between the propagated GTV and the manually delineated GTV is 0.885 ± 0.026, and the Hausdorff distance (HD) is \(2.93\,\pm \,0.93\) mm. In addition, the time for propagating GTV to all the phases is 3.67 ± 3.41 minutes. The results are better than fast adaptive stochastic gradient descent (FASGD) B-spline method, 3D+t B-spline method and diffeomorphic Demons method.

Conclusions

The proposed method is useful to help physicians delineate target volumes efficiently and accurately.

Keywords

Target volume delineation Contour propagation Deformable image registration Radiation therapy Lung cancer 

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Copyright information

© CARS 2016

Authors and Affiliations

  1. 1.Center for Biomedical Imaging and Bioinformatics, School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanChina
  2. 2.The Key Laboratory of Image Processing and Intelligent ControlMinistry of EducationWuhanChina
  3. 3.Cancer Center, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
  4. 4.Sino-US Intelligent Information Processing Joint LabAnyang Normal UniversityAnyangChina
  5. 5.Center for Machine Vision and Security ResearchKennesaw State UniversityKennesawUSA

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