Automated

ModularImageAnalysis (MIA) is an ImageJ plugin which provides a modular framework for assembling image and object analysis workflows. Detected objects can be transformed, filtered, measured and related. Analysis workflows are batch-enabled by default, allowing easy processing of high-content datasets.

MIA is designed for “out-of-the-box” compatibility with spatially-calibrated 5D images, yielding measurements in both pixel and physical units.  Functionality can be extended both internally, via integration with SciJava’s scripting interface, and externally, with Java modules that extend the MIA framework. Both have full access to all objects and images in the analysis workspace.

Workflows are, by default, compatible with batch processing multiple files within a single folder. Thanks to Bio-Formats, MIA has native support for multi-series image formats such as Leica .lif and Nikon .nd2.

Workflows can be automated from initial image loading through processing, object detection, measurement extraction, visualisation, and data exporting. MIA includes near 200 modules integrated with key ImageJ plugins such as Bio-Formats, TrackMate and Weka Trainable Segmentation.

Module(s) can be turned on/off dynamically in response to factors such as availability of images and objects, user inputs and measurement-based filters. Switches can also be added to “processing view” for easy workflow control.

MIA is developed in the Wolfson Bioimaging Facility at the University of Bristol.

ASTEC stands for Adaptive Segmentation and Tracking of Embryonic Cells. It proposes a full workflow for time lapse light sheet imaging analysis, including drift/motion compensation before the segmentation itself, and the capacity to correct for it.  It was used to process 3D+t movies acquired by the MuViSPIM light-sheet microscope in particular.

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.

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).

Removal of heterogeneous background from image data of single-molecule localization microscopy, using extreme value-based emitter recovery (EVER).

Quote:

EVER requires no manual adjustment of parameters and has been implemented as an easy-to-use ImageJ plugin that can immediately enhance the quality of reconstructed super-resolution images. This method is validated as an efficient way for robust nanoscale imaging of samples with heterogeneous background fluorescence, such as thicker tissue and cells.