Results 11 to 20 of about 682,217 (290)
Learning a Deformable Registration Pyramid
, 2021 We introduce an end-to-end unsupervised (or weakly supervised) image registration method that blends conventional medical image registration with contemporary deep learning techniques from computer vision. Our method downsamples both the fixed and the moving images into multiple feature map levels where a displacement field is estimated at each level ...
Niklas Gunnarsson +2 more
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Deformable image registration in radiation therapy [PDF]
Journal of Medical Radiation Sciences, 2020 Deformable image registration is an increasingly important method to account for soft tissue deformation between image acquisitions. This editorial discusses the clinical need and current status of deformable image registration.
Jason A Dowling, Laura M O’Connor
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Spatial deformable transformer for 3D point cloud registration
Scientific ReportsDeformable attention only focuses on a small group of key sample-points around the reference point and make itself be able to capture dynamically the local features of input feature map without considering the size of the feature map.
Fengguang Xiong +4 more
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Deformable and articulated 3D reconstruction from monocular video sequences [PDF]
, 2012 PhDThis thesis addresses the problem of deformable and articulated structure from motion from monocular uncalibrated video sequences. Structure from motion is defined as the problem of recovering information about the 3D structure of scenes imaged by a
Paladini, Marco
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Deformable image registration uncertainty quantification using deep learning for dose accumulation in adaptive proton therapy [PDF]
, 2022 Deformable image registration (DIR) is a key element in adaptive radiotherapy (AR) to include anatomical modifications in the adaptive planning. In AR, daily 3D images are acquired and DIR can be used for structure propagation and to deform the daily ...
Lomax, T. (author) +3 more
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Natural gradients for deformable registration [PDF]
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010 We apply the concept of natural gradients to deformable registration. The motivation stems from the lack of physical interpretation for gradients of image-based difference measures. The main idea is to endow the space of deformations with a distance metric which reflects the variation of the difference measure between two deformations.
Darko Zikic, Ali Kamen, Nassir Navab
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Groupwise Registration for Magnetic Resonance Image Based on Variational Inference
Chinese Journal of Magnetic Resonance, 2022 To address the low precision of pairwise registration method based on the deep learning and the time-consuming nature of traditional registration algorithm, this paper presents a method of unsupervised end-to-end groupwise registration based on ...
Qin ZHOU, Yuan-jun WANG
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Dense Registration with Deformation Priors [PDF]
, 2009 In this paper we propose a novel approach to define task-driven regularization constraints in deformable image registration using learned deformation priors. Our method consists of representing deformation through a set of control points and an interpolation strategy. Then, using a training set of images and the corresponding deformations we seek for a
Ben Glocker +4 more
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ADMIR–Affine and Deformable Medical Image Registration for Drug-Addicted Brain Images
IEEE Access, 2020 We proposed an unsupervised end-to-end Affine and Deformable Medical Image Registration (ADMIR) method based on convolutional neural network (ConvNet).
Kun Tang +4 more
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Registration Techniques for Deformable Objects
CoRR, 2021 In general, the problem of non-rigid registration is about matching two different scans of a dynamic object taken at two different points in time. These scans can undergo both rigid motions and non-rigid deformations. Since new parts of the model may come into view and other parts get occluded in between two scans, the region of overlap is a subset of ...
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