Deep Learning Methods Powered by AI in Tissue Image Analysis

CIO Applications recently sat down with our founder and CEO Michael Grunkin. The technology print magazine focuses on usage of various tech s

From tedious manual annotation work to fully automated annotations with a streamlined image analysis workflow. This is now possible with AI tools that are remarkably accurate generating powerful results within tissue segmentation, cell identification, quantification and other cell-based tasks.

AI expands the possibilities in cancer research and diagnostics

Whether you are looking for nuclei quantification in IHC images, accurate tumor separation in H&E, or advanced context aware region mapping in brain images, Oncotopix®/Biotopix™ AI image analysis is your go-to toolbox. Deep neural networks bring virtually endless possibilities to augmented pathology.

AI made easy

The Oncotopix®/Biotopix™ AI platform is train-by-example image analysis for digital pathology, made easy-to-use. Deep learning convolutional neural algorithms are trained based on easily annotated training data provided by you as the user. AI is not magic – you are in control of the learned behavior.

Patented virtual double stain (VDS)

Are you already using Artificial Intelligence (AI) for image analysis in digital pathology, and have you experienced the time-consuming task of annotating enough training data to capture the variance in your images? Let Visiopharm introduce you to our unique patented Virtual Double Stain (VDS) method for automatic annotation of training data.

AI redefines what is possible in image analysis

In more advanced cases robust identification of morphologically and/or functionally distinct features in histological samples, such as glomeruli in the kidney, compartments of the brain, and tumor/stroma separation, continues to challenge traditional image analysis methods. Differences in disease severity; preanalytical variables, such as variance in staining intensity; and structures or regions reliant solely on context often result in tedious manual annotations to achieve necessary accuracy.

Stefan Hamann, PhD from the Translational Pathology Laboratory at Biogen has utilized Visiopharm’s context-based deep learning algorithms to automate the laborious manual tissue annotation process. The task involved sagittal mouse brain sections with 6 regions-of-interest. The result is a fully automated mouse brain annotation tool that is remarkably accurate when confronted with unique tissue artifacts, illuminating the possibilities of deep learning within a streamlined image analysis workflow.

Visiopharm’s AI webinar

Watch our webinar to experience Oncotopix®/Biotopix™ AI image analysis with real-life applications, where Visiopharm’s deep learning experts demonstrate the “how to” with explanations and relevant demo cases.

Visiopharm AI image analysis solution

The Oncotopix® and Biotopix™ AI image analysis modules are available and fully integrated with the Visiopharm current image analysis software platform. Visit visiopharm.com/ai-deeplearning

Visiopharm AI Image Analysis in the news

Please see the launch news at TissuePathology: Keith Kaplans Digital Pathology Blog