Publication of SimSearch study demonstrating values of AI in microscopy

We are happy to announce the official publication of the study "SimSearch: A Human-in-the-loop learning framework for fast detection of regions of interest in microscopy images”, demonstrating Vironova’s technology leadership in AI-based research for bio-image applications in academia-industry collaborations.

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 publisihed in the IEEE Journal of Biomedical and Health Informatics:
IEEE J Biomed Health Inform. 2022 Aug;26(8):4079-4089. doi: 10.1109/JBHI.2022.3177602. Epub 2022 Aug 11.

The study 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.

Read the publication (IEEE Journal of Biomedical and Health Informatics)

15 August, 2022