A Generalization of Free-Form Deformation Image Registration Within the ITK Finite Element Framework

2006 ◽  
pp. 238-246 ◽  
Author(s):  
Nicholas J. Tustison ◽  
Brian B. Avants ◽  
Tessa A. Sundaram ◽  
Jeffrey T. Duda ◽  
James C. Gee
Keyword(s):  
Finite Element ◽  
Image Registration ◽  
Free Form ◽  
Free Form Deformation

scholarly journals Interactive Multigrid Refinement for Deformable Image Registration

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Wu Zhou ◽  
Yaoqin Xie
Keyword(s):  
Image Registration ◽  
Medical Images ◽  
Salient Feature ◽  
Deformable Image Registration ◽  
Free Form ◽  
Reference Image ◽  
Free Form Deformation ◽  
Feature Based ◽  
Automatic Algorithm ◽  
Overlapping Region

Deformable image registration is the spatial mapping of corresponding locations between images and can be used for important applications in radiotherapy. Although numerous methods have attempted to register deformable medical images automatically, such as salient-feature-based registration (SFBR), free-form deformation (FFD), and demons, no automatic method for registration is perfect, and no generic automatic algorithm has shown to work properly for clinical applications due to the fact that the deformation field is often complex and cannot be estimated well by current automatic deformable registration methods. This paper focuses on how to revise registration results interactively for deformable image registration. We can manually revise the transformed image locally in a hierarchical multigrid manner to make the transformed image register well with the reference image. The proposed method is based on multilevel B-spline to interactively revise the deformable transformation in the overlapping region between the reference image and the transformed image. The resulting deformation controls the shape of the transformed image and produces a nice registration or improves the registration results of other registration methods. Experimental results in clinical medical images for adaptive radiotherapy demonstrated the effectiveness of the proposed method.

scholarly journals A Comparative Evaluation of 3 Different Free-Form Deformable Image Registration and Contour Propagation Methods for Head and Neck MRI: The Case of Parotid Changes During Radiotherapy

2017 ◽  
Vol 16 (3) ◽  
pp. 373-381 ◽  
Author(s):  
Sara Broggi ◽  
Elisa Scalco ◽  
Maria Luisa Belli ◽  
Gerlinde Logghe ◽  
Dirk Verellen ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Image Registration ◽  
Head And Neck ◽  
Deformable Image Registration ◽  
Similarity Coefficient ◽  
Free Form ◽  
Dice Similarity Coefficient ◽  
Contour Propagation ◽  
Free Form Deformation ◽  
Symmetric Distance

Purpose: To validate and compare the deformable image registration and parotid contour propagation process for head and neck magnetic resonance imaging in patients treated with radiotherapy using 3 different approaches—the commercial MIM, the open-source Elastix software, and an optimized version of it. Materials and Methods: Twelve patients with head and neck cancer previously treated with radiotherapy were considered. Deformable image registration and parotid contour propagation were evaluated by considering the magnetic resonance images acquired before and after the end of the treatment. Deformable image registration, based on free-form deformation method, and contour propagation available on MIM were compared to Elastix. Two different contour propagation approaches were implemented for Elastix software, a conventional one (DIR_Trx) and an optimized homemade version, based on mesh deformation (DIR_Mesh). The accuracy of these 3 approaches was estimated by comparing propagated to manual contours in terms of average symmetric distance, maximum symmetric distance, Dice similarity coefficient, sensitivity, and inclusiveness. Results: A good agreement was generally found between the manual contours and the propagated ones, without differences among the 3 methods; in few critical cases with complex deformations, DIR_Mesh proved to be more accurate, having the lowest values of average symmetric distance and maximum symmetric distance and the highest value of Dice similarity coefficient, although nonsignificant. The average propagation errors with respect to the reference contours are lower than the voxel diagonal (2 mm), and Dice similarity coefficient is around 0.8 for all 3 methods. Conclusion: The 3 free-form deformation approaches were not significantly different in terms of deformable image registration accuracy and can be safely adopted for the registration and parotid contour propagation during radiotherapy on magnetic resonance imaging. More optimized approaches (as DIR_Mesh) could be preferable for critical deformations.

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