Journal ArticleDOI
elastix : A Toolbox for Intensity-Based Medical Image Registration
Reads0
Chats0
TLDR
The software consists of a collection of algorithms that are commonly used to solve medical image registration problems, and allows the user to quickly configure, test, and compare different registration methods for a specific application.Abstract:
Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.read more
Citations
More filters
Journal ArticleDOI
A reproducible evaluation of ANTs similarity metric performance in brain image registration.
TL;DR: This is the first study to use a consistent transformation framework to provide a reproducible evaluation of the isolated effect of the similarity metric on optimal template construction and brain labeling, and to quantify the similarity of templates derived from different subgroups.
Journal ArticleDOI
Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging.
TL;DR: More robust estimates of the proportion of affected voxels, the number of fiber orientations within each WM voxel, and the impact on tensor‐derived analyses are provided, using large, high‐quality diffusion‐weighted data sets, with reconstruction parameters optimized specifically for this task.
Journal ArticleDOI
Medical image registration: a review.
TL;DR: The aim of this paper is to be an introduction to the field, provide knowledge on the work that has been developed and to be a suitable reference for those who are looking for registration methods for a specific application.
Journal ArticleDOI
VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images
TL;DR: An auto‐context version of the VoxResNet is proposed by combining the low‐level image appearance features, implicit shape information, and high‐level context together for further improving the segmentation performance, and achieved the best performance in the 2013 MICCAI MRBrainS challenge.
Journal ArticleDOI
Multi-Atlas Segmentation of Biomedical Images: A Survey
TL;DR: Multi-atlas segmentation (MAS) is becoming one of the most widely used and successful image segmentation techniques in biomedical applications as mentioned in this paper, and it has been widely used in medical image classification.
References
More filters
Journal ArticleDOI
Nonrigid registration using free-form deformations: application to breast MR images
TL;DR: The results clearly indicate that the proposed nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.
Journal ArticleDOI
Principal warps: thin-plate splines and the decomposition of deformations
TL;DR: The decomposition of deformations by principal warps is demonstrated and the method is extended to deal with curving edges between landmarks to aid the extraction of features for analysis, comparison, and diagnosis of biological and medical images.
Journal ArticleDOI
Multimodality image registration by maximization of mutual information
TL;DR: The results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved completely automatically and without any prior segmentation, feature extraction, or other preprocessing steps which makes this method very well suited for clinical applications.
Journal ArticleDOI
A survey of image registration techniques
TL;DR: This paper organizes this material by establishing the relationship between the variations in the images and the type of registration techniques which can most appropriately be applied, and establishing a framework for understanding the merits and relationships between the wide variety of existing techniques.