A dedicated module for NIS-Elements, utilizing convolutional neural networks (CNNs) to learn from human-assisted tracing of small subset of representative samples and then apply the neural network to recognize patterns automatically.
Produce low-noise microscopic images with short exposure times.
Allows users to capture images with short exposure times without sacrificing signal-to-noise, thus expanding practical applications for low-light imaging.
Predict and produce virtual fluorescent images from DIC/ phase-contrast images of unstained specimen
Enable non-destructive, analysis of unstained and live sample
Trained to distinguish structures of interest that cannot easily be defined by classic thresholding and image processing like neurites and dead