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In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements. Computer vision is the science and technology of machines that see. ...
For other uses, see Data (disambiguation). ...
Medical image registration (e.g. for data of the same patient taken at different points in time) often additionally involves elastic (or nonrigid) registration to cope with deformation of the subject (due to breathing, anatomical changes, etc.). Nonrigid registration of medical images can also be used to register a patient's data to an anatomical atlas, such as the Talairach atlas for neuroimaging. Medical imaging designates the ensemble of techniques and processes used to create images of the human body (or parts thereof) for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and function). ...
Jean Talairach was a neurosurgeon who practiced at the Centre Hospitalier Ste. ...
Algorithm classifications
Area-based vs Feature-based Image registration algorithms fall within two realms of classification: area based methods and feature based methods. The original image is often referred to as the reference image and the image to be mapped onto the reference image is referred to as the target image. For area based image registration methods, the algorithm looks at the structure of the image via correlation metrics, Fourier properties and other means of structural analysis. However, most feature based methods, instead of looking at the overall structure of images, fine tunes its mapping to the correlation of image features: lines, curves, points, line intersections, boundaries, etc.
Transformation model Image registration algorithms can also be classified according to the transformation model used to relate the reference image space with the target image space. The first broad category of transformation models includes linear transformations, which are a combination of translation, rotation, global scaling, shear and perspective components. Linear transformations are global in nature, thus not being able to model local deformations. Usually, perspective components are not needed for registration, so that in this case the linear transformation is an affine one. In mathematics, a linear transformation (also called linear map or linear operator) is a function between two vector spaces that preserves the operations of vector addition and scalar multiplication. ...
In mathematics, a linear transformation (also called linear map or linear operator) is a function between two vector spaces that preserves the operations of vector addition and scalar multiplication. ...
The second category includes 'elastic' or 'nonrigid' transformations. These transformations allow local warping of image features, thus providing support for local deformations. Nonrigid transformation approaches include polynomial wrapping, interpolation of smooth basis functions (thin-plate splines and wavelets), and physical continuum models (viscous fluid models and large deformation diffeomorphisms). One type of spline, a bézier curve In the mathematical subfield of numerical analysis, a spline is a special function defined piecewise by polynomials. ...
A wavelet is a kind of mathematical function used to divide a given function into different frequency components and study each component with a resolution that matches its scale. ...
In mathematics, a diffeomorphism is a kind of isomorphism of smooth manifolds. ...
Search-based vs direct methods Image registration methods can also be classified in terms of the type of search that is needed to compute the transformation between the two image domains. In search-based methods the effect of different image deformations is evaluated and compared. In direct methods, such as the Lucas Kanade method and phase-based methods, an estimate of the image deformation is computed from local image statistics and is then used for updating the estimated image deformation between the two domains. Lucas-Kanade method of estimating optical flow Optical flow methods try to calculate the motion between two image frames which are taken at times t and at every pixel position. ...
Spatial-domain methods Many image registration methods operate in the spatial domain, using features, structures, and textures as matching criteria. In the spatial domain, images look 'normal' as the human eye might perceive them. Some of the feature matching algorithms are outgrowths of traditional techniques for performing manual image registration, in which operators choose matching sets of control points (CPs) between images. When the number of control points exceeds the minimum required to define the appropriate transformation model, iterative algorithms like RANSAC are used to robustly estimate the best solution. RANSAC is an abbreviation for RANdom SAmple Consensus. It is an algorithm to estimate parameters of a mathematical model from a set of observed data which contains outliers. ...
Frequency-domain methods Other algorithms use the properties of the frequency-domain to directly determine shifts between two images. Applying the Phase correlation method to a pair of overlapping images produces a third image which contains a single peak. The location of this peak corresponds to the relative translation between the two images. Unlike many spatial-domain algorithms, the phase correlation method is resilient to noise, occlusions, and other defects typical of medical or satellite images. Additionally, the phase correlation uses the Fast fourier transform to compute the cross-correlation between the two images, generally resulting in large performance gains. The method can be extended to determine affine rotation and scaling between two images by first converting the images to log-polar coordinates. Due to properties of the Fourier transform, the rotation and scaling parameters can be determined in a manner invariant to translation. This single feature makes phase-correlation methods highly attractive vs. typical spatial methods, which must determine rotation, scaling, and translation simultaneously, often at the cost of reduced precision in all three. Phase correlation is a frequency domain approach to determine the relative translative movement between two images. ...
The Fast Fourier Transform (FFT) is an efficient algorithm to compute the discrete Fourier transform (DFT) and its inverse. ...
In geometry, an affine transformation or affine map (from the Latin, affinis, connected with) between two vector spaces (strictly speaking, two affine spaces) consists of a linear transformation followed by a translation: In the finite-dimensional case each affine transformation is given by a matrix A and a vector b...
In mathematics, the Fourier transform is a certain linear operator that maps functions to other functions. ...
Image nature Another useful classification is between single-modality and multi-modality registration algorithms. Single-modality registration algorithms are those intended to register images of the same modality (i.e. acquired using the same kind of imaging device), while multi-modality registration algorithms are those intended to register images acquired using different imaging devices.
There are several examples of multi-modality registration algorithms in the medical imaging field. Examples include registration of brain CT/MRI images or whole body PET/CT images for tumor localization, registration of contrast-enhanced CT images against non-contrast-enhanced CT images for segmentation of specific parts of the anatomy and registration of ultrasound and CT images for prostate localization in radiotherapy. Medical imaging designates the ensemble of techniques and processes used to create images of the human body (or parts thereof) for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and function). ...
negron305 Cat scan redirects here. ...
The mri are a fictional alien species in the Faded Sun Trilogy of C.J. Cherryh. ...
Image of a typical positron emission tomography (PET) facility Positron emission tomography (PET) is a nuclear medicine medical imaging technique which produces a three-dimensional image or map of functional processes in the body. ...
negron305 Cat scan redirects here. ...
negron305 Cat scan redirects here. ...
negron305 Cat scan redirects here. ...
For other uses, see Ultrasound (disambiguation). ...
negron305 Cat scan redirects here. ...
The prostate is a compound tubuloalveolar exocrine gland of the male mammalian reproductive system. ...
Radiation therapy (or radiotherapy) is the medical use of ionizing radiation as part of cancer treatment to control malignant cells (not to be confused with radiology, the use of radiation in medical imaging and diagnosis). ...
Other classifications Further ways of classifying an algorithm consist of the amount of data it is optimized to handle, the algorithm's application, and the central theory the algorithm is based around. Image registration has applications in remote sensing (cartography updating), medical imaging (change detection, tumor monitoring), and computer vision. Due to the vast applications to which image registration can be applied, it's impossible to develop a general algorithm optimized for all uses. Medical imaging designates the ensemble of techniques and processes used to create images of the human body (or parts thereof) for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and function). ...
Image similarity-based methods Image similarity-based methods are broadly used in medical imaging. A basic image similarity-based method consists of a transformation model, which is applied to reference image coordinates to locate their corresponding coordinates in the target image space, an image similarity metric, which quantifies the degree of correspondence between features in both image spaces achieved by a given transformation, and an optimization algorithm, which tries to maximize image similarity by changing the transformation parameters. Medical imaging designates the ensemble of techniques and processes used to create images of the human body (or parts thereof) for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and function). ...
In mathematics, a transformation in elementary terms is any of a variety of different functions from geometry, such as rotations, reflections and translations. ...
Given two or more images of the same 3D scene, taken from different points of view, the correspondence problem is to find a set of points in one image which can be indentified as the same points in another image. ...
In mathematics, the term optimization, or mathematical programming, refers to the study of problems in which one seeks to minimize or maximize a real function by systematically choosing the values of real or integer variables from within an allowed set. ...
The choice of an image similarity measure depends on the nature of the images to be registered. Common examples of image similarity measures include Cross-correlation, Mutual information, Mean-square difference and Ratio Image Uniformity. Mutual information and its variant, Normalized Mutual Information, are the most popular image similarity measures for registration of multimodality images. Cross-correlation, Mean-square difference and Ratio Image Uniformity are commonly used for registration of images of the same modality. In statistics, the term cross-correlation is sometimes used to refer to the covariance cov(X, Y) between two random vectors X and Y, in order to distinguish that concept from the covariance of a random vector X, which is understood to be the matrix of covariances between the scalar...
In probability theory and, in particular, information theory, the mutual information, or transinformation, of two random variables is a quantity that measures the mutual dependence of the two variables. ...
In probability theory and, in particular, information theory, the mutual information, or transinformation, of two random variables is a quantity that measures the mutual dependence of the two variables. ...
Open source software Several open source software packages are available for performing image registration Open source refers to projects that are open to the public and which draw on other projects that are freely available to the general public. ...
In computer programming, ITK is a cross-platform application development framework, widely used for the development of image segmentation and image registration programs. ...
GemIdent logo GemIdent is an interactive image processing program that identifies regions of interest. ...
See also Image File history File links Free_Software_Portal_Logo. ...
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