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New scientific publication showing Vironova’s technology leadership in AI research

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New scientific publication showing Vironova’s technology leadership in AI research for bioimage applications and engagement in academic-industry collaboration. Access the paper ahead of print. 

The paper entitled “ SimSearch: A Human-in-the-loop learning framework for fast detection of regions of interest in microscopy images” with authors from Uppsala University, Astra Zeneca and Vironova AB has been accepted to IEEE Journal of Biomedical and Health Informatics.

The paper presents a framework for quick and easy user-guided training and customization of deep neural network models aimed at fast detection of objects or regions of interest in large-scale microscopy experiments. SimSearch is designed to help biologists quickly and with minimal user input extract informative regions and perform analyses on large sets of image data.

The framework presented in this paper is an important contribution to making AI methods useful and trustworthy in real world microscopy applications, says Vironova’s CTO Ida-Maria Sintorn, last author of the paper.

ACCESS TO THE PAPER AHEAD OF PRINT