Estimate geometric transformation that aligns two 2-D or 3-D images
estimates the geometric transformation that aligns the moving image
tform = imregtform(
moving with the fixed image
transformType is a string scalar or character vector that
defines the type of transformation to estimate.
optimizer is an
object that describes the method for optimizing the metric.
metric is an object that defines the quantitative measure
of similarity between the images to optimize. The output
is a geometric transformation object that maps
estimates the geometric transformation where
tform = imregtform(
Rfixed specify the spatial referencing objects associated
fixed images. The
tform is a geometric transformation object in units
defined by the spatial referencing objects
Estimate Transformation Needed for Image Registration
Read two images. This example uses two magnetic resonance (MRI) images of a knee. The fixed image is a spin echo image, while the moving image is a spin echo image with inversion recovery. The two sagittal slices were acquired at the same time but are slightly out of alignment.
fixed = dicomread('knee1.dcm'); moving = dicomread('knee2.dcm');
View the misaligned images.
Create the optimizer and metric, setting the modality to
'multimodal' since the images come from different sensors.
[optimizer, metric] = imregconfig('multimodal')
optimizer = registration.optimizer.OnePlusOneEvolutionary Properties: GrowthFactor: 1.050000e+00 Epsilon: 1.500000e-06 InitialRadius: 6.250000e-03 MaximumIterations: 100
metric = registration.metric.MattesMutualInformation Properties: NumberOfSpatialSamples: 500 NumberOfHistogramBins: 50 UseAllPixels: 1
Tune the properties of the optimizer to get the problem to converge on a global maxima and to allow for more iterations.
optimizer.InitialRadius = 0.009; optimizer.Epsilon = 1.5e-4; optimizer.GrowthFactor = 1.01; optimizer.MaximumIterations = 300;
Find the geometric transformation that maps the image to be registered (
moving) to the reference image (
tform = imregtform(moving, fixed, 'affine', optimizer, metric)
tform = affine2d with properties: T: [3x3 double] Dimensionality: 2
Apply the transformation to the image being registered (
moving) using the
imwarp function. The example uses the
'OutputView' parameter to preserve world limits and resolution of the reference image when forming the transformed image.
movingRegistered = imwarp(moving,tform,'OutputView',imref2d(size(fixed)));
View the registered images.
figure imshowpair(fixed, movingRegistered,'Scaling','joint')
moving — Image to be registered
2-D or 3-D grayscale image
Image to be registered, specified as a 2-D or 3-D grayscale image.
fixed — Reference image in the target orientation
2-D or 3-D grayscale image
Reference image in the target orientation, specified as a 2-D or 3-D grayscale image.
transformType — Geometric transformation to be applied to the image to be registered
Geometric transformation to be applied to the image to be registered, specified as one of the following values:
|Rigid transformation consisting of translation and rotation.|
|Nonreflective similarity transformation consisting of translation, rotation, and scale.|
|Affine transformation consisting of translation, rotation, scale, and shear.|
types always involve nonreflective transformations.
Specify optional pairs of arguments as
the argument name and
Value is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Before R2021a, use commas to separate each name and value, and enclose
Name in quotes.
'DisplayOptimization',1 enables verbose
DisplayOptimization — Verbose optimization flag
false (default) |
Verbose optimization flag, specified as the comma-separated
pair consisting of
'DisplayOptimization', and the
imregister displays optimization
information in the command window during the registration process.
PyramidLevels — Number of multi-level image pyramid levels used during the registration process
3 (default) | positive integer
Number of pyramid levels used during the registration process,
specified as the comma-separated pair consisting of
a positive integer.
'PyramidLevels',4 sets the number
of pyramid levels to
When you have spatial referencing information available, it is important to provide this information to
imregtform, using spatial referencing objects. This information helps
imregtformconverge to better results more quickly because scale differences can be considered.
imregisteruse the same underlying registration algorithm.
imregisterperforms the additional step of resampling
movingto produce the registered output image from the geometric transformation estimate calculated by
imregtformwhen you want access to the geometric transformation that relates
imregisterwhen you want a registered output image.
Getting good results from optimization-based image registration usually requires modifying optimizer and/or metric settings for the pair of images being registered. The
imregconfigfunction provides a default configuration that should only be considered a starting point. See the output of the
imregconfigfor more information on the different parameters that can be modified.