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Automated quantification of steatosis: agreement with stereological point counting
Authors:André Homeyer  Patrik Nasr  Christiane Engel  Stergios Kechagias  Peter Lundberg  Mattias Ekstedt  Henning Kost  Nick Weiss  Tim Palmer  Horst Karl Hahn  Darren Treanor  Claes Lundström
Affiliation:1.Fraunhofer MEVIS,Bremen,Germany;2.Center for Medical Image Science and Visualization, Link?ping University,Link?ping,Sweden;3.Department of Medical and Health Sciences,Link?ping University,Link?ping,Sweden;4.Department of Radiation Physics,Link?ping University,Link?ping,Sweden;5.Institute of Cancer and Pathology, University of Leeds,Leeds,UK;6.Leeds Teaching Hospitals NHS Trust,Leeds,UK
Abstract:

Background

Steatosis is routinely assessed histologically in clinical practice and research. Automated image analysis can reduce the effort of quantifying steatosis. Since reproducibility is essential for practical use, we have evaluated different analysis methods in terms of their agreement with stereological point counting (SPC) performed by a hepatologist.

Methods

The evaluation was based on a large and representative data set of 970 histological images from human patients with different liver diseases. Three of the evaluated methods were built on previously published approaches. One method incorporated a new approach to improve the robustness to image variability.

Results

The new method showed the strongest agreement with the expert. At 20× resolution, it reproduced steatosis area fractions with a mean absolute error of 0.011 for absent or mild steatosis and 0.036 for moderate or severe steatosis. At 10× resolution, it was more accurate than and twice as fast as all other methods at 20× resolution. When compared with SPC performed by two additional human observers, its error was substantially lower than one and only slightly above the other observer.

Conclusions

The results suggest that the new method can be a suitable automated replacement for SPC. Before further improvements can be verified, it is necessary to thoroughly assess the variability of SPC between human observers.
Keywords:
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