Results 1 to 10 of about 2,531,473 (178)
Locally Orderless Registration [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 Image registration is an important tool for medical image analysis and is used to bring images into the same reference frame by warping the coordinate field of one image, such that some similarity measure is minimized.
Darkner, Sune, Sporring, Jon
core +8 more sources
Subspace-Based Holistic Registration for Low-Resolution Facial Images [PDF]
, 2010 Subspace-based holistic registration is introduced as an alternative to landmark-based face registration, which has a poor performance on low-resolution images, as obtained in camera surveillance applications.
Boom, B.J. +2 more
core +4 more sources
Validating Dose Uncertainty Estimates Produced by AUTODIRECT: An Automated Program to Evaluate Deformable Image Registration Accuracy. [PDF]
, 2017 Deformable image registration is a powerful tool for mapping information, such as radiation therapy dose calculations, from one computed tomography image to another. However, deformable image registration is susceptible to mapping errors.
Chen, Josephine +5 more
core +3 more sources
Finite element surface registration incorporating curvature, volume preservation, and statistical model information [PDF]
, 2013 We present a novel method for nonrigid registration of 3D surfaces and images. The method can be used to register surfaces by means of their distance images, or to register medical images directly.
Albrecht, Thomas +3 more
core +4 more sources
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1998 Summary Functional data analysis involves the extension of familiar statistical procedures such as principal components analysis, linear modelling, and canonical correlation analysis to data where the raw observation xi is a function. An essential preliminary to a functional data analysis is often the registration or alignment of salient
Ramsay, J. O., Li, Xiaochun
openaire +2 more sources
Robust point correspondence applied to two and three-dimensional image registration [PDF]
, 2002 Accurate and robust correspondence calculations are very important in many medical and biological applications. Often, the correspondence calculation forms part of a rigid registration algorithm, but accurate correspondences are especially important for ...
Baldock, R. A. +4 more
core +1 more source
Adversarial Deformation Regularization for Training Image Registration Neural Networks [PDF]
, 2018 We describe an adversarial learning approach to constrain convolutional neural network training for image registration, replacing heuristic smoothness measures of displacement fields often used in these tasks.
Barratt, Dean C. +8 more
core +2 more sources
A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration
, 2018 Image registration, the process of aligning two or more images, is the core technique of many (semi-)automatic medical image analysis tasks. Recent studies have shown that deep learning methods, notably convolutional neural networks (ConvNets), can be ...
Berendsen, Floris F. +5 more
core +2 more sources
Learning Rigid Image Registration - Utilizing Convolutional Neural Networks for Medical Image Registration [PDF]
, 2018 Many traditional computer vision tasks, such as segmentation, have seen large step-changes in accuracy and/or speed with the application of Convolutional Neural Networks (CNNs).
Goatman, K.A. +2 more
core +1 more source
, 2018 The goal of image registration is to find a 1-1 point-wise correspondence between two images, a subject image and a target image. Knowing the pointwise correspondence between two brain images allows comparison of structural and functional imaging data such as regions of interest, functional data (e.g., fMRI, EEG, MEG, DTI), and geometric shapes.
openaire +2 more sources