ImageJ Macros

The BioVoxxel Toolbox is a suite which contains plugins and some macros dealing with image filtering, image segmentation and binary image processing and analysis. The following plugins are hosted here:

• Extended Particle Analyzer
• Binary Feature Extractor
• Speckle Inspector
• Watershed Irregular Features
• EDM Binary Operations
• Filter Check
• Pseudo flat-field correction
• Convoluted Background Subtraction
• 2D Particle Distribution (Distribution_Analysis)
• Cluster Indicator
• SSIDC Cluster Indicator
• Gaussian weighted Median filter
• Adaptive Filter
• Enhance True Color Contrast
• Mode and Differential Limited Mean Binarization
• Basic Recursive Filter

Fast4DReg is a Fiji macro for drift correction for 2D and 3D video and is able to correct drift in all x-, y- and/or z-directions. Fast4DReg creates intensity projections along both axes and estimates their drift using cross-correlation based drift correction, and then translates the video frame by frame. Additionally, Fast4DReg can be used for alignment multi-channel 2D or 3D images which is particularly useful for instruments that suffer from a misalignment of channels.

This workflow describes a deep-learning based pipeline for reliable single-organoid segmentation and tracking in 2D+t high-resolution brightfield microscopy of mouse mammary epithelial organoids. The pipeline involves a four-layer U-Net to infer semantic segmentation predictions, adaptive morphological filtering to establish candidate organoid instances, and a shape-similarity-constrained, instance-segmentation-correcting tracking step to associate the corresponding organoid instances in time.

It is particularly focused on automatically detecting an organoid located approximately in the center of the first frame and track all its subsequent instances in the remaining frames, emphasizing on accurate organoid boundary delineation. Furthermore, segmentation network was trained using plausible pix2pixHD-generated bioimage data. Syntheric image simulator code and data are also available here.

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.