16 September 2019

Histopathologic assessment of kidney tissue currently relies on manual scoring or traditional image-processing techniques to quantify and classify tissue features. These approaches are time-consuming and have limited reproducibility.

Meyke Hermsen, theme Renal disorders, Jeroen van der Laak, theme Women's cancers, and colleagues, present an alternative approach, featuring a convolutional neural network (CNN) for multi-class segmentation of periodic acid–Schiff (PAS)-stained kidney tissue sections.

Their work was published online this week by the Journal of the American Society of Nephrology.

Meyke Hermsen: 

Jeroen van der Laak:

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