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20192026
most citedResolving challenges in deep learning-based analyses of histopathological images using explanation methods

167 citations · 223 across the 13 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

eess.IV2023★ 9 cited

DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology

Marco Aversa, Gabriel Nobis, Miriam Hägele +10

We present DiffInfinite, a hierarchical diffusion model that generates arbitrarily large histological images while preserving long-range correlation structural information. Our app…

cs.CV2023

Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides

Miriam Hägele, Johannes Eschrich, Lukas Ruff +6

In this paper, we present a deep learning segmentation approach to classify and quantify the two most prevalent primary liver cancers - hepatocellular carcinoma and intrahepatic ch…