Image correction

A deep-learning solution for stain color normalization in digital histology images

Estimate the positions and spacing between sections (or at local points) of three dimensional image data. This method may be applied to any imaging modality that acquires 3-dimensional data as a stack of 2-dimensional sections. We provide plugins for both Fiji and TrakEM2.

Workflow of data-analysis strategies for image-based cell profiling.

1. Image analysis (image correction, image segmentation, feature extraction)
2. Image quality control
3. Preprocessing extracted features
4. Dimensionality reduction
5. Single-cell data aggregation
6. Measuring profile similarity
7. Assay quality assessment
8. Downstream analysis

Examples of publications where the workflow has been used at least partly:

• Image-based multivariate profiling of drug responses from single cells
• Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes
• Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping
• Cell shape and the microenvironment regulate nuclear translocation of NF‐κB in breast epithelial and tumor cells
• Genome-wide RNAi Screening Identifies Protein Modules Required for 40S Subunit Synthesis in Human Cells
• Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes
• Systematic morphological profiling of human gene and allele function via Cell Painting

This macro implements a filter that is meant to attenuate close to parallel intensity stripes in an image, such as often happening in light sheet microscopy. The results are usually decent even when the stripes show a large angular spread due to light sheet refraction at the sample surface. The filter can process a 3D stack but the processing is performed slice by slice.

Example image is available in the documentation link. 

Acquiarium is for carrying out the common pipeline of many spatial cell studies using fluorescence microscopy. It addresses image capture, raw image correction, image segmentation, quantification of segmented objects and their spatial arrangement, volume rendering, and statistical evaluation. It is focused on quantification of spatial properties of many objects and their mutual spatial relations in a collection of many 3D images. It can be used for analysis of a collection of 2D images or time lapse series of 2D or 3D images as well. It has a modular design and is extensible via plug-ins. It is a stand-alone, easy to install application written in C++ language. The GUI is written using cross-platform wxWidgets library.