Rigid registration

Automatic registration in 2D or 3D based on detection or binary mask. Takes images with detections already done on it.

This plugin allows to compute a similarity (translation/rotation/scaling and flipping) transform from pair of points. It is updating the transformed image interactively such that the user get immediate feedback. The transformation is saved and can be applied to any other stack/image. Non rigid deformation can also be applied in 2D or 3D.

3D/3D,2D/3D or 3D /2D can be handled .

3D ROI are enabled, and can be checked with the 3D vtk view (size of ROI can be changed using the ROI stroke width).

Some prealignment by rotating in 3D the volume is possible.

Transformations can be applied directly or combined through Block Protocols (search for apply transformation).

It's also provide information about the predicted Error (based on statistical prediction), either as a full color mapping, either on each points used as landmarks, and error on the discrepancy in position between points.

There are video tutorials available in the web.

- 2D Stabilization in each slice of the stacks in time. - 3D Stabilization intravital imaging of all the stacks (including the dimension Z) - create the videos and the stabilized images in a new folder 2701

The ICP algorithm takes two point clouds as an input and return the rigid transformation (rotation matrix R and translation vector T), that best aligns the point clouds. Example: [R,T] = icp(q,p,10); Aligns the points of p to the points q with 10 iterations of the algorithm. The transformation is then applied using R*p + repmat(T,1,length(p)); The file has implemented both point to point and point to plane as well as a couple of other features such as extrapolation, weighting functions, edge point rejection, etc.

Align aligns images relative to each other, for example, to correct shifts in the optical path of a microscope in each channel of a multi-channel set of images.

For two or more input images, this module determines the optimal alignment among them. Aligning images is useful to obtain proper measurements of the intensities in one channel based on objects identified in another channel, for example. Alignment is often needed when the microscope is not perfectly calibrated. It can also be useful to align images in a time-lapse series of images. The module stores the amount of shift between images as a measurement, which can be useful for quality control purposes.

Note that the second image (and others following) is always aligned with respect to the first image. That is, the X/Y offsets indicate how much the second image needs to be shifted by to match the first. This module does not perform warping or rotation, it simply shifts images in X and Y. For more complex registration tasks, you might preprocess images using a plugin for that purpose in FIJI/ImageJ.

| Supports 2D? | Supports 3D? | Respects masks? |
|--------------|--------------|-----------------| | Yes | No | Yes |

Measurements made by this module

• Xshift, Yshift: The pixel shift in X and Y of the aligned image with respect to the original image.

References

• Lewis JP. (1995) “Fast normalized cross-correlation.” Vision Interface, 1-7.