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Automated Quantitation of Steatosis, Fibrosis and Ballooning Using Machine Learning in Routine Histological Images of Liver Biopsies of Patients with NAFLD

Year: 2018

Type: conference-paper

Abstract: Background: Histology remains the gold standard for diagnosis of Non-Alcoholic Fatty Liver Disease.It is reported using semi-quantitative scores, with high intra and inter-observer variability.Ballooning is a key histological feature in Non-Alcoholic Steatohepatitis (NASH), however its diagnosis is still challenging.We aimed to develop an automated method based on machine learning for the quantitation of ballooning, fat and fibrosis using routine histological images of patients with NAFLD.

Source: Spiral (Imperial College London)

Authors: Forlano, R, Giannakeas, N, Mullish, BH, Tsipouras, M, Tzallas, A, Yee, M, Lloyd, J, Goldin, RD, Thursz, MR, Manousou, P

Institutions: Imperial College London, Technological Educational Institute of Athens, Imperial College Healthcare NHS Trust

Language: English

Topic: Liver Disease Diagnosis and Treatment

Subfield: Hepatology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7064437674

FWCI:

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Related to: 10