a high throughput
image processing application
Quantify thousands of images
using your individual processing pipelines
ImageC highlights
Fast processing pipelines for big data sets
ImageC is implemented in C++, one of the fastest programming languages and efficiently uses all available CPU resources (multi threading support). With the focus on hight throughput analyzes, ImageC allows processing times down to 0.2 seconds per image, allowing the analysis of thousands of images in a reasonable time.
Read moreAnalysis of fluorescence and brightfield images
ImageC enables object detection and quantification in fluorescence images. Analysis and cross channel quantification can be applied to any number of channels. e.g. Measurement of fluorescence intensity per cell.
Read moreAnalysis of histological images
ImageC enables the analysis of huge histological images, taken by fluorescence and light microscopy. e.g.: Color picker enables to distinguish cellular compartments based on color.
Read moreBioFormats support
All common image formats used by different microscope manufacturers are supported thanks to BioFormats integration.
Read moreMulti channel images
ImageC automatically extracts underlying image infos (e.g. channel infos, Z-stack infos, etc. ) using OME-XML which allows to directly use multi channel (c, t and z-stack) images.
Read moreBig data organization
ImageC stores all the pipeline results into an integrated in-process SQL database (DuckDb) using a predefined data structure. The flexibility of the database matched with an easy to use GUI enables basic data postprocessing and comparison.
Read moreData export
The data are stored as an compressed database file and can be exported for further processing to R or Excel. Custom export templates can be used for the creation of individual data sets.
Read moreImage/Data grouping
Automated image grouping based on well formats, image names using regex or directory structure can help to organize data output. AVG, MEDIAN, MAX, MIN, STDEV, SUM and CNT are automatically calculated from multiple images within a group.
Read moreImage/Data Filtering
ImageC allows to define data filters, removing images from the report based on customized criteria. e.g. remove Images without cells.
Read moreHeatmaps
ImageC can generate heatmaps of images or image groups (e.g. plates. wells), enabling a quick assessment of the data.
Read moreInteractive results
Browse through your results to see the selected objects in the original image. The interactive mode allows really to observe each individual detected object within the origin image.
Read morePipeline creation
ImageC enables the creation of individual image processing pipelines for object detection. A set of widely used image processing algorithms ported from ImageJ, including background subtraction algorithms, filtering, edge detection and manual as well as auto-threshold are implemented and can be used for pipeline creation.
Read moreLive preview
ImageC offers a live preview enabling to monitor the impact of all image processing steps within the pipelines and thereby provides transparent and understandable object detection.
Read moreAI driven object detection
In addition to classical image processing and thresholding algorithms ImageC supports object detection and classification based on AI. ImageC supports the ONNX container format with net hight and with of 640 x 640 and a stride size of 3.
Read moreGeneration of control images
ImageC generates user defined control images, for documentation and internal control.
Read morePipeline templates
EVAnalyzer and its successor ImageC where created within a research group focused on extracellular vesicles. ImageC provides powerful pipelines especially for single vesicle imaging applications.
Read moreDistance measurement
The ImageC distance measurement feature automatically calculates distances across different object classes. Together with time frame support, this enables the quantification of low-level object tracking.
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