title: A finite element method to correct deformable image registration errors in low-contrast regions.
abstract: Image-guided adaptive radiotherapy requires deformable image registration to map radiation dose back and forth between images. The purpose of this study is to develop a novel method to improve the accuracy of an intensity-based image registration algorithm in low-contrast regions. A computational framework has been developed in this study to improve the quality of the 'demons' registration. For each voxel in the registration's target image, the standard deviation of image intensity in a neighborhood of this voxel was calculated. A mask for high-contrast regions was generated based on their standard deviations. In the masked regions, a tetrahedral mesh was refined recursively so that a sufficient number of tetrahedral nodes in these regions can be selected as driving nodes. An elastic system driven by the displacements of the selected nodes was formulated using a finite element method (FEM) and implemented on the refined mesh. The displacements of these driving nodes were generated with the 'demons' algorithm. The solution of the system was derived using a conjugated gradient method, and interpolated to generate a displacement vector field for the registered images. The FEM correction method was compared with the 'demons' algorithm on the computed tomography (CT) images of lung and prostate patients. The performance of the FEM correction relating to the 'demons' registration was analyzed based on the physical property of their deformation maps, and quantitatively evaluated through a benchmark model developed specifically for this study. Compared to the benchmark model, the 'demons' registration has the maximum error of 1.2 cm, which can be corrected by the FEM to 0.4 cm, and the average error of the 'demons' registration is reduced from 0.17 to 0.11 cm. For the CT images of lung and prostate patients, the deformation maps generated by the 'demons' algorithm were found unrealistic at several places. In these places, the displacement differences between the 'demons' registrations and their FEM corrections were found in the range of 0.4 and 1.1 cm. The mesh refinement and FEM simulation were implemented in a single thread application which requires about 45 min of computation time on a 2.6 GHz computer. This study has demonstrated that the FEM can be integrated with intensity-based image registration algorithms to improve their registration accuracy, especially in low-contrast regions.
authors.affiliation: Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA. hzhong1@hfhs.org
authors.forename: Hualiang
authors.initials: H
authors.lastname: Zhong
authors.forename: Jinkoo
authors.initials: J
authors.lastname: Kim
authors.forename: Haisen
authors.initials: H
authors.lastname: Li
authors.forename: Teamour
authors.initials: T
authors.lastname: Nurushev
authors.forename: Benjamin
authors.initials: B
authors.lastname: Movsas
authors.forename: Indrin J
authors.initials: IJ
authors.lastname: Chetty
mesh_terms: D016477:Artifacts; D054893:Cone-Beam Computed Tomography; D020342:Finite Element Analysis; D056973:Four-Dimensional Computed Tomography; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging; D008297:Male; D011467:Prostate / Q000000981:diagnostic imaging