A coarse-to-fine deformable transformation framework for unsupervised multi-contrast MR image registration with dual consistency constraint
Multi-contrast magnetic resonance (MR) image registration is useful in the clinic to achieve
fast and accurate imaging-based disease diagnosis and treatment planning. Nevertheless …
fast and accurate imaging-based disease diagnosis and treatment planning. Nevertheless …
AMNet: Adaptive multi-level network for deformable registration of 3D brain MR images
Abstract Three-dimensional (3D) deformable image registration is a fundamental technique
in medical image analysis tasks. Although it has been extensively investigated, current deep …
in medical image analysis tasks. Although it has been extensively investigated, current deep …
HCS-Net: Multi-level deformation strategy combined with quadruple attention for image registration
Z Ou, X Lu, Y Gu - Computers in Biology and Medicine, 2024 - Elsevier
Background and objective Non-rigid image registration plays a significant role in computer-
aided diagnosis and surgical navigation for brain diseases. Registration methods that utilize …
aided diagnosis and surgical navigation for brain diseases. Registration methods that utilize …
Transmatch: A transformer-based multilevel dual-stream feature matching network for unsupervised deformable image registration
Feature matching, which refers to establishing the correspondence of regions between two
images (usually voxel features), is a crucial prerequisite of feature-based registration. For …
images (usually voxel features), is a crucial prerequisite of feature-based registration. For …
Difficulty-aware hierarchical convolutional neural networks for deformable registration of brain MR images
The aim of deformable brain image registration is to align anatomical structures, which can
potentially vary with large and complex deformations. Anatomical structures vary in size and …
potentially vary with large and complex deformations. Anatomical structures vary in size and …
Unsupervised deep feature learning for deformable registration of MR brain images
Establishing accurate anatomical correspondences is critical for medical image registration.
Although many hand-engineered features have been proposed for correspondence …
Although many hand-engineered features have been proposed for correspondence …
Robust deformable image registration using cycle-consistent implicit representations
LD Van Harten, J Stoker, I Išgum - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recent works in medical image registration have proposed the use of Implicit Neural
Representations, demonstrating performance that rivals state-of-the-art learning-based …
Representations, demonstrating performance that rivals state-of-the-art learning-based …
Deformable MR-CT image registration using an unsupervised, dual-channel network for neurosurgical guidance
Purpose The accuracy of minimally invasive, intracranial neurosurgery can be challenged
by deformation of brain tissue–eg, up to 10 mm due to egress of cerebrospinal fluid during …
by deformation of brain tissue–eg, up to 10 mm due to egress of cerebrospinal fluid during …
Non-iterative coarse-to-fine registration based on single-pass deep cumulative learning
Deformable image registration is a crucial step in medical image analysis for finding a non-
linear spatial transformation between a pair of fixed and moving images. Deep registration …
linear spatial transformation between a pair of fixed and moving images. Deep registration …
Deformable medical image registration with global–local transformation network and region similarity constraint
Deformable medical image registration can achieve fast and accurate alignment between
two images, enabling medical professionals to analyze images of different subjects in a …
two images, enabling medical professionals to analyze images of different subjects in a …