Results 11 to 20 of about 30,960 (188)

Deformable image registration in radiation therapy [PDF]

open access: yesJournal 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
openaire   +2 more sources

A Multistage Rigid-Affine-Deformable Network for Three-Dimensional Multimodal Medical Image Registration

open access: yesApplied Sciences, 2023
Multimodal image registration is an important component of medical image processing, allowing the integration of complementary information from various imaging modalities to improve clinical applications like diagnosis and treatment planning. We proposed
Anika Strittmatter   +2 more
doaj   +1 more source

Edge-Aware Pyramidal Deformable Network for Unsupervised Registration of Brain MR Images

open access: yesFrontiers in Neuroscience, 2021
Deformable image registration is of essential important for clinical diagnosis, treatment planning, and surgical navigation. However, most existing registration solutions require separate rigid alignment before deformable registration, and may not well ...
Yiqin Cao   +7 more
doaj   +1 more source

Mid-space-independent deformable image registration [PDF]

open access: yesNeuroImage, 2017
Aligning images in a mid-space is a common approach to ensuring that deformable image registration is symmetric - that it does not depend on the arbitrary ordering of the input images. The results are, however, generally dependent on the mathematical definition of the mid-space.
Aganj, Iman   +4 more
openaire   +5 more sources

A review of deep learning-based deformable medical image registration

open access: yesFrontiers in Oncology, 2022
The alignment of images through deformable image registration is vital to clinical applications (e.g., atlas creation, image fusion, and tumor targeting in image-guided navigation systems) and is still a challenging problem.
Jing Zou   +3 more
doaj   +1 more source

Deformable Medical Image Registration: A Survey [PDF]

open access: yesIEEE Transactions on Medical Imaging, 2013
Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical ...
Sotiras, Aristeidis   +2 more
openaire   +3 more sources

macJNet: weakly-supervised multimodal image deformable registration using joint learning framework and multi-sampling cascaded MIND

open access: yesBioMedical Engineering OnLine, 2023
Deformable multimodal image registration plays a key role in medical image analysis. It remains a challenge to find accurate dense correspondences between multimodal images due to the significant intensity distortion and the large deformation. macJNet is
Zhiyong Zhou   +6 more
doaj   +1 more source

ADMIR–Affine and Deformable Medical Image Registration for Drug-Addicted Brain Images

open access: yesIEEE 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
doaj   +1 more source

Canny edge-based deformable image registration [PDF]

open access: yesPhysics in Medicine and Biology, 2017
This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information.
Vasant, Kearney   +4 more
openaire   +2 more sources

Deformable image registration in radiation therapy [PDF]

open access: yesRadiation Oncology Journal, 2017
The number of imaging data sets has significantly increased during radiation treatment after introducing a diverse range of advanced techniques into the field of radiation oncology. As a consequence, there have been many studies proposing meaningful applications of imaging data set use.
Oh, Seungjong, Kim, Siyong
openaire   +2 more sources

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