AI-driven Automated Imaging

Image Processing with Sophisticated Deep Learning Algorithms
Discover Our Applications Supported by Deep Neural Networks (DNNs)

Karyotyping Becomes Faster And More Convenient with DNN

Karyotyping by means of Deep Neural Networks (DNNs) is already in routine use. The most common techniques for chromosome banding and various tissue types are supported. With DNN based algorithms, fewer corrective interactions are necessary to generate the final karyogram. Applying this technology to suitable specimen and imaging hardware, the turnaround time per case can be significantly reduced.

The entire karyotyping workflow can be automated with MetaSystems to simplify the workflow management and achieve a high level of standardization. Metaphase finding and image acquisition can be done fully automated driven by Metafer. Metaphase images are directly imported into the Ikaros software. DNN based algorithms support our customers in chromosome separation and karyogram assignment by providing an automated karyogram proposal.¹

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Intelligent Karyotyping

Automation of Forensic Sperm Detection Leads to More Efficiency

The tedious search for sperm cells in forensic samples can be simplified and standardized with the help of DNN based software algorithms. Manual detection of sperm cells is a thing from the past with MetaSystems. Sophisticated deep learning algorithms based on Deep Neural Networks (DNNs) standardize and automate the detection of sperm cells.

Forensic specimen processed with “Christmas Tree” (Nuclear Fast Red/Picroindigocarmine) staining are supported in the automated workflow. An objective slide can be scanned in less than 15 minutes with suitable imaging hardware and specimen preparation. Object coordinates of sperm cells are stored and, if wanted, easily transferred to laser micro-dissection systems.²

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Automated Forensic Sperm Detection

Intelligent Classification of White Blood Cells Eases Cell Counting

The visual inspection of white blood cells allows the detection of even subtle changes in cell morphology. The automated imaging workflow by MetaSystems for the classification of white blood cells is fast and offers a high potential for standardization.

We apply Deep Neural Networks (DNNs), a method in artificial intelligence, to facilitate image acquisition and image processing. The suggested classification of cells can be easily reviewed by an expert in the convenient display of the Metafer software. Metafer automatically updates the counted numbers per cell type. Diagrams with the counts of different cell types can be customized in the software display and reporting function of Metafer.²

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More Applications

Deep Neural Networks (DNNs) are a powerful technology in medicine and life sciences. MetaSystems is currently developing DNNs for various applications in automated microscopy imaging. We will announce all news and advances on our website and through our social media channels.

Visit our Applications section to find out more about automated imaging in Cytogenetics, Cancer Biology, Cell Biology, Pathology, Toxicology, Radiation Biology, Microbiology, Forensics, and more.