Deep learning-based molecular morphometrics for kidney biopsies
M. Zimmermann, M. Klaus, M. N. Wong, A.-K. Thebille, L. Gernhold, C. Kuppe, M. Halder, J. Kranz, N. Wanner, F. Braun, S. Wulf, T. Wiech, U. Panzer, C. F. Krebs, E. Hoxha, , V. G. Puelles
The paper develops a deep learning method for analyzing kidney biopsy images to quantify podocyte loss, identifying morphometric signatures in ANCA-GN patients for risk stratification.
bioRxiv · Aug 23, 2020Pathology