Results 1 - 10 of 3,593

Image registration methods: a survey.

by Barbara Zitová , Jan Flusser , 2003
"... Abstract This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrical ..."
Abstract - Cited by 760 (10 self) - Add to MetaCart
geometrically align two images (the reference and sensed images). The reviewed approaches are classified according to their nature (areabased and feature-based) and according to four basic steps of image registration procedure: feature detection, feature matching, mapping function design, and image

An iterative image registration technique with an application to stereo vision

by Bruce D. Lucas, Takeo Kanade - In IJCAI81 , 1981
"... Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of Newton- ..."
Abstract - Cited by 2897 (30 self) - Add to MetaCart
. The registration problem The translational image registration problem can be characterized as follows: We are given functions F(x) and G(x) which give the respective pixel values at each location x in two images, where x is a vector. We wish to find the disparity vector h which minimizes some measure

Nonrigid registration using free-form deformations: Application to breast MR images

by D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, D. J. Hawkes - IEEE Transactions on Medical Imaging , 1999
"... Abstract — In this paper we present a new approach for the nonrigid registration of contrast-enhanced breast MRI. A hierarchical transformation model of the motion of the breast has been developed. The global motion of the breast is modeled by an affine transformation while the local breast motion i ..."
Abstract - Cited by 697 (36 self) - Add to MetaCart
is described by a free-form deformation (FFD) based on B-splines. Normalized mutual information is used as a voxel-based similarity measure which is insensitive to intensity changes as a result of the contrast enhancement. Registration is achieved by minimizing a cost function, which represents a combination

Lucas-Kanade 20 Years On: A Unifying Framework: Part 3

by Simon Baker, Ralph Gross, Iain Matthews - International Journal of Computer Vision , 2002
"... Since the Lucas-Kanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms hav ..."
Abstract - Cited by 706 (30 self) - Add to MetaCart
Since the Lucas-Kanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms

Gradient based optimization of an emst image registration function

by Mert R. Sabuncu, Peter J. Ramadge - In Intl. Conf. Acoust., Speech Sig. Proc , 2005
"... This paper examines the problem of registering images using an information theoretic metric (e.g., entropy) estimated using a Euclidean Minimum Spanning Tree (EMST). The objective is to find an extremum of the metric with respect to a vector of free parameters. One of the major difficulties posed by ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
also indicate how this can be used for optimizing image registration over a vector set of parameters

Unified segmentation

by John Ashburner, Karl J. Friston , 2005
"... A probabilistic framework is presented that enables image registration, tissue classification, and bias correction to be combined within the same generative model. A derivation of a log-likelihood objective function for the unified model is provided. The model is based on a mixture of Gaussians and ..."
Abstract - Cited by 324 (12 self) - Add to MetaCart
A probabilistic framework is presented that enables image registration, tissue classification, and bias correction to be combined within the same generative model. A derivation of a log-likelihood objective function for the unified model is provided. The model is based on a mixture of Gaussians

A Pyramid Approach to Sub-Pixel Registration Based on Intensity

by Philippe Thevenaz, Urs Ruttiman, Michal Unser , 1998
"... We present an automatic sub-pixel registration algorithm that minimizes the mean square intensity difference between a reference and a test data set, which can be either images (2-D) or volumes (3-D). It uses an explicit spline representation of the images in conjunction with spline processing, and ..."
Abstract - Cited by 237 (18 self) - Add to MetaCart
restricted to rigid-body motion (rotation and translation), combined with isometric scaling. It also includes an optional adjustment of image contrast differences. We obtain excellent results for the registration of intra-modality Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging

registration

by Girish Gopalakrishnan, Timothy Poston, Nithin Nagaraj, Rakesh Mullick
"... function-based phantoms for evaluation of ..."
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function-based phantoms for evaluation of

RESEARCH Open Access Motion correction of whole-body PET data with a joint PET-MRI registration functional

by Michael Fieseler, Fabian Gigengack, Xiaoyi Jiang, Klaus P Schäfers
"... Respiratory motion is known to degrade image quality in PET imaging. The necessary acquisition time of several minutes per bed position will inevitably lead to a blurring effect due to organ motion. A lot of research has been done with regards to motion correction of PET data. As full-body PET-MRI b ..."
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to increase motion estimation robustness and precision. In this work we propose a registration functional that is capable of performing motion detection in gated data of two modalities simultaneously. Evaluation is performed using phantom data. We demonstrate that performing a joint registration of both

Shape Distributions

by Robert Osada, Thomas Funkhouser, Bernard Chazelle, David Dobkin - ACM Transactions on Graphics , 2002
"... this paper, we propose and analyze a method for computing shape signatures for arbitrary (possibly degenerate) 3D polygonal models. The key idea is to represent the signature of an object as a shape distribution sampled from a shape function measuring global geometric properties of an object. The pr ..."
Abstract - Cited by 295 (2 self) - Add to MetaCart
this paper, we propose and analyze a method for computing shape signatures for arbitrary (possibly degenerate) 3D polygonal models. The key idea is to represent the signature of an object as a shape distribution sampled from a shape function measuring global geometric properties of an object
Results 1 - 10 of 3,593