In modern biological microscopy, fluorescence imaging is used to record and quantify location, functional status, and abundance of a tagged target molecule. This requires the application of image correction techniques and calibration methods for both image visualization and quantitative analysis. Digital image processing algorithms and softwares for correction and calibration strategies are discussed in the following sections.
It is the ideal "glue" for easily integrating dissimilar fluorescent microscope hardware and peripherals into a single custom workstation, while providing all the tools needed to perform meaningful analysis of acquired images. The software offers many user-friendly application modules for biology-specific analysis such as cell signaling, cell counting, and protein expression.
Analyzes, processes and visualizes multi-dimensional microscopy images. BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes.
Allows users to detect and count fluorescent signals in microscopy images of cells. Blob Finder is a free software that performs two types of analysis: (i) an average count, for quantifying the number of nuclei and signals in an image; (ii) and a single cell analysis, that assigns each signal to the closest cell and get a signal count for each cell in the image. It also performs on-z_stacks of the cell with a maximum projection to project the image data into a 2D image.
Restores images from microscopic data. Huygens is based on the deconvolution approach that reassigns out-of-focus light to its origin, thus improves signal-to-noise in images. It can use physically-acquired or simulated point-spread functions (PSFs) for characterization of optical system being deconvolved. The tool shows high-performance in in-house tests on deconvolution compared to other software packages. It provides intuitive wizards for parameter selection and processing.
Allows to work on both fixed-cell and dynamic live-cell super resolution using conventional fluorophores compatible with a variety of imaging modalities. SRRF provides a significant reduction in reconstruction artefacts, such as the disappearance of structures or ringing effects while remaining computationally efficient. It permits virtually any laboratory access to super-resolution imaging.
Increases the local contrast of an image. CLAHE uses the contrast limited adaptive histogram equalization to process. The contrast amplification in the vicinity of a given pixel value is delivered by the slope of the transformation function. This ImageJ plugin has three main parameters: block size, histogram and max slope.
Corrects image defects caused by uneven illumination in fluorescent microscopy. Background Correction is an ImageJ plugin that can realize several tasks: (1) it generates a background image estimated through iterations of the minimum ranking with the number of iterations defined by the user; (2) it subtracts the background image from the original image; and (3) it generates a result image.