Image registration

Image registration is the process of transforming 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 sensors/imaging modalities, at different times, from different view points, etc. . Registration can be based on correspondence established between the landmarks or feature points. Alternatively, some similarity/distance metric is established between the image intensity maps to navigate the registration process.

Synonyms
Image alignment
Description

The MIPAV (Medical Image Processing, Analysis, and Visualization) application enables quantitative analysis and visualization of medical images of numerous modalities such as PET, MRI, CT, or microscopy. Using MIPAV's standard user-interface and analysis tools, researchers at remote sites (via the internet) can easily share research data and analyses, thereby enhancing their ability to research, diagnose, monitor, and treat medical disorders.

Description

ANTs computes high-dimensional mappings to capture the statistics of brain structure and function.

Image Registration

Diffeomorphisms: SyN, Independent Evaluation: Klein, Murphy, Template Construction (2004)(2010), Similarity Metrics, Multivariate registration, Multiple modality analysis and statistical bias

Image Segmentation

Atropos Multivar-EM Segmentation (link), Multi-atlas methods (link) and JLF, Bias Correction (link), DiReCT cortical thickness (link), DiReCT in chimpanzees

 

Advanced Normalization Tools
Description

A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O.

The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction; EPI unwarping), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear model).

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Description

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.

Description

SliceMap

Whole brain tissue slices are commonly used in neurobiological research for analyzing pathological features in an anatomically defined manner. However, since many pathologies are expressed in specific regions of the brain, it is necessary to have an annotation of the regions in the brain slices. Such an annotation can be done by manual delineation, as done most often, or by an automated region annotation tool.

SliceMap is a FIJI/ImageJ plugin for automated brain region annotation of fluorescent brain slices. The plugin uses a reference library of pre-annotated brain slices (the brain region templates) to annotate brain regions of unknown samples. To perform the region annotation, SliceMap registers the reference slices to the sample slice (using elastic registration plugin BUnwarpJ) and uses the resulting image transformations to morph the template regions towards the anatomical brain regions of the sample. The resulting brain regions are saved as FIJI/ImageJ ROI’s (Regions Of Interest) as a single zip-file for each sample slice.

More information can also be found in "SliceMap: an algorithm for automated brain region annotation", Michaël Barbier, Astrid Bottelbergs, Rony Nuydens, Andreas Ebneth, Winnok H De Vos, Bioinformatics, btx658, https://doi.org/10.1093/bioinformatics/btx658

Example: SliceMaps brain region segmentation