Segmentation of Lipid Droplets in Histological Images

Daniel Budelmann, Cao Qing, Hendrik Oliver Laue, Mohamed Albadry, Uta Dahmen, Lars Ole Schwen

Keywords: Hepatic steatosis, histology, whole-slide images, nnU-Net, segmentation.

TL;DR: Automatic steatosis quantification in histological whole slide HE stained slides.

Abstract:

Steatosis is a common liver disease characterized by the accumulation of lipid droplets
in cells. Precise and reliable fat droplet identification is essential for automatic steatosis
quantification in histological images. We trained a nnU-Net to automatically segment lipid
vacuoles in whole-slide images using semi-automatically generated reference annotations.
We evaluated the performance of the trained model on two out-of-distribution datasets.
The trained model’s average F1 scores (0.801 and 0.804) suggest a high potential of the
nnU-Net framework for the automatic segmentation of lipid vacuoles.