Unsupervised learning for deformable registration of thoracic CT and cone‐beam CT based on multiscale features matching with spatially adaptive weighting

2020 ◽  
Vol 47 (11) ◽  
pp. 5632-5647
Author(s):  
Luwen Duan ◽  
Xinye Ni ◽  
Qi Liu ◽  
Lun Gong ◽  
Gang Yuan ◽  
...  
Keyword(s):  
Unsupervised Learning ◽  
Cone Beam Ct ◽  
Deformable Registration ◽  
Cone Beam ◽  
Adaptive Weighting ◽  
Thoracic Ct ◽  
Spatially Adaptive

scholarly journals Fully Convolutional Network for Consistent Voxel-Wise Correspondence

2020 ◽  
Vol 34 (07) ◽  
pp. 12935-12942 ◽  
Author(s):  
Yungeng Zhang ◽  
Yuru Pei ◽  
Yuke Guo ◽  
Gengyu Ma ◽  
Tianmin Xu ◽  
...  
Keyword(s):  
Vector Fields ◽  
State Of The Art ◽  
Displacement Vector ◽  
Cone Beam Ct ◽  
Deformable Registration ◽  
Cone Beam ◽  
Nonlinear Mapping ◽  
Convolutional Network ◽  
Mapping Functions ◽  
Fully Convolutional Network

In this paper, we propose a fully convolutional network-based dense map from voxels to invertible pair of displacement vector fields regarding a template grid for the consistent voxel-wise correspondence. We parameterize the volumetric mapping using a convolutional network and train it in an unsupervised way by leveraging the spatial transformer to minimize the gap between the warped volumetric image and the template grid. Instead of learning the unidirectional map, we learn the nonlinear mapping functions for both forward and backward transformations. We introduce the combinational inverse constraints for the volumetric one-to-one maps, where the pairwise and triple constraints are utilized to learn the cycle-consistent correspondence maps between volumes. Experiments on both synthetic and clinically captured volumetric cone-beam CT (CBCT) images show that the proposed framework is effective and competitive against state-of-the-art deformable registration techniques.

SU-FF-I-103: A Segmentation-Based Deformable Registration Algorithm for Cone Beam CT and Helical CT Images

2009 ◽  
Vol 36 (6Part4) ◽  
pp. 2458-2458
Author(s):  
X Li ◽  
T Li ◽  
Y Yang ◽  
D Heron ◽  
M Huq
Keyword(s):  
Cone Beam Ct ◽  
Helical Ct ◽  
Ct Images ◽  
Deformable Registration ◽  
Cone Beam ◽  
Registration Algorithm
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