Biologists are increasingly seeking an advanced techniques to perform live-cell imaging experiments. In respond to the growing demand, Image ExFluorer proposes AI technology that facilitates data analysis for researchers at the forefront of the bio industry.
The powerful combination of Image Exfluorer and AI analytical software aid to provide researchers with customized solutions and convenience to address your tough tasks in less time.
Thanks to AI analysis, it enables to capture fine details of a variety of cellular assays with flexible fluorescent microscopy. It recovers contrast to signal-to-noise for comprehensive cell reignition and improve data accuracy by leveraging AI training.
Our systems for high-contents imaging and analytical tools are highly tailorable and making it easy to evolve your system alongside your research quick and effortless
Remove blur from the existing wild-field microscopes to implement the shape of real cells through a pre-trained algorithm by Clarify AI.
The module recognizes fluorescence signal emitted from out-of-focus planes and can computationally remove this haze component from the image automatically
It is difficult to define the cell areas by conventional method if there is not much difference between the cell and background signal.
By utilizing Segment AI, the network can learn and apply segmentation to similar images which helps to accurately set up the cell region through various criteria.
By learning the certain patterns in two different channels; Brightfield and Fluorescent image, the network can be trained to predict the fluorescent channel by only brightfield image is acquired. This predicted channel by Predict AI enables cell counting or segmentation without stained or harmful light excitation.
Some fluorescent samples express a low signal that is difficult to visualize or segment.
By Restore AI, the network can be trained to restore the details for some underexposed sensitive samples without photobleached or photodamage.
General Analysis 3(GA3)
GA3 creates a playground for integrated process from imaging to analysis and data management. Users can build algorithms that fit their user objectivity by linking desired functions to the image. Through these tasks, a number of images can be performed in an integrated manner according to the specified algorithm.