Leveraging weak complementary labels enhances semantic segmentation of hepatocellular carcinoma and intrahepatic cholangiocarcinoma

Leveraging weak complementary labels enhances semantic segmentation of hepatocellular carcinoma and intrahepatic cholangiocarcinoma

Abstract 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 cholangiocarcinoma – from hematoxylin and eosin (H&E) stained whole slide images. While semantic segmentation...

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Main Authors: Miriam Hägele, Johannes Eschrich, Lukas Ruff, Maximilian Alber, Simon Schallenberg, Adrien Guillot, Christoph Roderburg, Frank Tacke, Frederick Klauschen
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-75256-w
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https://doi.org/10.1038/s41598-024-75256-w

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