Microscopy Image Analysis with Deep-Learning Technology

Imaging Software Microscopy Image Analysis with Deep-Learning Technology

26.01.2018Editor: Doris Popp

Leveraging the power of deep learning, Olympus Cellsens imaging software for microscopy offers significantly improved segmentation analysis, such as label-free nucleus detection and cell counting, for more accurate data and efficient experiments.

Related Company

Olympus Deutschland GmbH

Olympus cellSens imaging software
(Source: Olympus)

Image analysis is a critical part of many life science applications. Analyses that rely on segmentation to extract targets, such as cells and organelles, from the rest of the image are commonplace. However, conventional thresholding methods that depend on brightness and color can miss critical information or may not be able to detect the targets at all. Cellsens software’s deep-learning technology enables users to quickly train the system to automatically capture this information, improving the speed and accuracy of label-free object detection, quantitative analysis of fluorescent-labeled cells and segmentation based on morphological features.

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Imaging Software Microscopy Image Analysis with Deep-Learning Technology

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