Digital Image Analysis
Smart Structure Recognition
Power of DEEP Learning
In-vitro neurons, glial cells, astrocytes
In-vitro on CHIP
– Upload up to 6 images from the same sample
– Give us an email contact to send you DEMO feedback
Leave short instructions (image with marks and/or narrative explanation) about what do you want to measure from images
– build a custom protocol for your image analysis needs
– send you back DEMO materials :
** Researchers on COVID-19 topics, we are here to help!
Examples of DEMO materials:
providing additional information regarding the expectations, probability, and efficiency of all the steps of analysis.
Fast analysis of a larger set of images
KARMENstudio team - committed to bringing solutions to help researchers.
We have a core team of 7 dedicated scientists, entrepreneurs, and developers. Led by:
KARMENstudio team -bringing smart structure recognition solutions for research purposes.
The main workflow consists of base preprocessing, segmentation and classification with integrated functional modules and features, mapping and statistics.
Image analysis workflow includes following steps:
Deep Learning allows fast and efficient image analysis containing complex visual structures. In addition, thanks to Deep Learning, we can also quickly develop novel analysis scripts for new applications through automated proposing patterns of new scripts, based on our extensive experiential database, and adjusting the parameters of the new script modules.
Full analysis of a typical 8-megapixel image with resolution 3266×2450 pixels rarely takes more than 2 seconds on an average computer today.
Developing a novel script module for new applications takes only a few weeks.
Our image analysis is oriented to work with many related images, such as individual images forming a large visual scene, or a sequence of images captured in a short time, or slow time lapse of images, or images taken as cross-sections of 3D digitized objects.
This multiple-image orientation is ensured for high-speed image analysis and high data optimization, which enables simultaneous access and handling of even extremely large amounts of data.
KARMENstudio is highly modular and easily upgradable for different applications.
Upgrade models include plugins with new segmentation and classification functionalities, as well as plugin extensions for preprocessing, multiple image processing, structural analysis and data analysis.
Intuitive interface allows easy interactivity during all image analysis steps.
In the case of segmentation and classification it is possible to return to any previous intermediate step from the script, and to make adjustments to the parameters of the modules.
While the initial scope of KARMENstudio was developed for life-science microscopy, in particular in the field of cellular neuroscience, KARMENstudio has a much wider scope today, thanks to its distinct modularity and upgradability.
Examples of image processing modules used in KARMENstudio are: Structural analysis of bones and keypoint detection, Object tracing due to moving affinities, Point Spread Function detection, Validation by segment registration with other image analysis tools.