Image stitching

It stitches 3D tiles from terabyte-size microscopy datasets. Stitching does not require any prior information on the actual positions of the tiles, sample fiducials, or conversion of raw TIFF images, and the stitched images can be explored instantly.

MosaicExplorerJ was specifically designed to process lightsheet microscopy datasets from optically cleared samples. It can handle multiple fluorescence channels, dual-side lightsheet illumination and dual-side camera detection.

ClearMap is a toolbox for the analysis and registration of volumetric data from cleared tissues.

It was initially developed to map brain activity at cellular resolution in whole mouse brains using immediate early gene expression. It has since then been extended as a tool for the qunatification of whole mouse brain vascualtur networks at capilary resolution.

It is composed of sevral specialized modules or scripts: tubemap, cellmap, WobblyStitcher.

ClearMap has been designed to analyze O(TB) 3d datasets obtained via light sheet microscopy from iDISCO+ cleared tissue samples immunolabeled for proteins. The ClearMap tools may also be useful for data obtained with other types of microscopes, types of markers, clearing techniques, as well as other species, organs, or samples.

Voxelytic-Align is a commercial software provided as a service on cloud targetted to electron microscopy reconstruction (alignement, artifact correction...)

Hot-Knife is a library specifically designed for FIB-SEM data and thick sections, which includes code for flattening, deformable alignment with features and a more robust kind of block-matching, and some visualization, manual correction, and import and export tools (n5).

A collection of Java tools and HTTP services (APIs) for rendering transformed image tiles that includes:

• a JSON data model for render, tile, and transform specifications,
• a Java stand-alone render application / library,
• a set of render web services that provide RESTful APIs to persisted collections of tile and transform specifications, and
• a set of Java clients for processing/rendering data that utilize the render web services to retrieve and/or store persisted specifications.
• Docker packaging for building the libraries and deploying the render web services

The basic concept is to render images (tiles) based on transformation files, without having to store the big generated image from an alignment of tiles (mosaicking).

Reconstruct big images from overlapping tiled images on a Spark cluster.

The code is based on the Stitching plugin for Fiji https://github.com/fiji/Stitching

TeraStitcher is a free tool that enables the stitching of Teravoxel-sized tiled microscopy images even on workstations with relatively limited resources of memory (<8 GB) and processing power. It exploits the knowledge of approximate tile positions and uses ad-hoc strategies and algorithms designed for such very large datasets. The produced images can be saved into a multiresolution representation to be efficiently visualized (e.g. Vaa3D-TeraFly) and processed.

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.

XuvTools (pronounced “ex-you-vee-tools”) is a fully automated 3D stitching software for biomedical image data, typically confocal microscopy images. XuvTools runs on Microsoft Windows XP and Vista, Linux and Apple Mac computers. It supports 32 and 64bit operating systems (with 64bit highly preferred). XuvTools is free and open source software (see Licensing), so you can start using it immediately. Go to Downloads and give it a try. The goal of XuvTools is to provide tools, that combine multiple microscopic recordings to obtain a larger field of view (“stitching”) and a higher dynamic range (“HDR” recombination), or better resolution (multi view reconstruction), and to make these tools publicly available.

SlideToolkit is a collection of command-line tools to assist with the automated histology analysis of whole-slide images. The publication linked in the "reference" details the actual workflow. 

This includes tools to organize the data, perform tiling and subsequent batch processing of the generated tiles in a cell profiler pipeline. All the tools are designed to run on a single PC or on a HPC system. The scripts in the toolkit are on github under MIT licence.

This macro can stitch a (Z,T,C) data set with virtually no limit on the number of Z slices and time frames. The input to the macro is a folder with the raw tiff images (one image per file) as typically exported by motorized microscopes. These files must all be stores in the same folder and the file naming should ideally comply to OME-TIFF. The macro is however quite flexible: Only --X, --Y and --Z fields with user defined number of digits are compulsory. --T, --C and --L fields with user defined number of digits are necessary for multiple time frames / channels data sets. A compatible data set is provided as a .zip archive. Before processing it unzip it to a given location. The stitching is performed in a reference Z slice (and in a specific reference time frame and channel). The same displacements are applied to all the Z slices, time frames and channels. Before starting the batch processing a montage with the original images of the selected Z slice / time frame / channel is displayed together with the stitched image in this stack. If you are not satisfied with the result you can select another reference. The stitching is then performed time frame by time frame and slice by slice and the stitched images are exported to a single user defined output folder. The macro can also process a data set with multiple channels, the stitching is then computed once on a reference channel and then applied to the other channels.

This macro builds a stitched image from a muti-position 3D + time hyperstack. The XY positions of the montage should be coded as channels in the input hyperstack. Channel ordering can be configured in the dialog box to adapt to Column/Row and Meander/Comb configurations: The images should appear in this order when browsing the hyperstack with the channel slider. Fine stitching is supported (requires sufficient overlap between the views). The XY displacements of each field of view for stitching are computed for a single reference (Z,T) slice (user configurable) and applied to all slices (Z and T).

This plugin facilitates the assembly of a mosaic of overlapping individual images, or tiles. It provides a semi-automated solution where the initial rough positioning of the tiles must be performed by the user, and where the final delicate adjustments are performed by the plugin.

The MosaicJ plugin requires that a second plugin, named TurboReg, is installed. 

TrakEM2 is an ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation (Fiji comes with TrakEM2). It supports arbitrary-sized datasets. 

This plugin has two components:

• Elastic Montage
  • montaging mosaics from overlapping tiles where the tiles have non-linear relative deformation
• Elastic Stack Alignment
  • alignment of deformed section series from serially sectioned volumes

The plugin performs stitching of images of a tiled scan to reconstruct the image of the whole sample.