Affine registration

The BigStitcher is a software package that allows simple and efficient alignment of multi-tile and multi-angle image datasets, for example acquired by lightsheet, widefield or confocal microscopes. The software supports images of almost arbitrary size ranging from very small images up to volumes in the range of many terabytes, which are for example produced when acquiring cleared tissue samples with lightsheet microscopy.

This is an example workflow of how to perform automatic registration by

- first detecting spots in both images using wavelet segmentation (with different scale according to the image scale)

- second using Ec-Clem autofinder to register both images

Click on a block to know more about a tool. Non referenced tools are non clickable.

quote:

Elastix cite{Klein2010} is an open source, command-line program for intensity-based registration of medical images that allows the user to quickly configure, test, and compare different registration methods. SimpleElastix is an extension of SimpleITK cite{Lowekamp2013} that allows you to configure and run Elastix entirely in Python, Java, R, Octave, Ruby, Lua, Tcl and C# on Linux, Mac and Windows. The goal is to bring robust registration algorithms to a wider audience and make it easier to use elastix, e.g. for Java-based enterprise applications or rapid Python prototyping.

Python example

import SimpleITK as sitk
resultImage = sitk.Elastix(sitk.ReadImage("fixedImage.nii"), sitk.ReadImage("movingImage.nii"))

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.