Computer Vision News 28 Best Paper Award at BVM Accurately measuring cell proliferation speed is important for understanding the aggressiveness of tumors. A key element in this assessment is the argyrophilic nucleolar organizer regions (AgNORs) found within cell nuclei, which are correlated with cell proliferation. More AgNORs mean faster proliferation. This paper explores the automatic assessment of AgNORs from histopathology images, paving the way for more precise and informed tumor diagnosis. Alongside other methods, such as Ki-67andcounting mitotic figures, AgNOR-scores offer an additional layer of explainability, shedding light on the pace at which cells divide. Marc Aubreville (left) is a professor at the Technical University Ingolstadt of Applied Sciences in Germany, where Jonathan Ganz (right) is a PhD student, with a co-supervisor at FAU ErlangenNürnberg. They speak to us fresh from winning the Best Paper Award at BVM 2023 last month. Deep Learning-Based Automatic Assessment of AgNOR-scores in Histopathology Images
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