Next Article in Journal
TESMA: Requirements and Design of a Tool for Educational Programs
Previous Article in Journal
Information and Symmetry: Adumbrating the Abstract Core of Complex Systems
Previous Article in Special Issue
Patients’ Admissions in Intensive Care Units: A Clustering Overview
Open AccessArticle

Automated Detection of Liver Histopathological Findings Based on Biopsy Image Processing

1
Department of Informatics & Telecommunications Engineering, University of Western Macedonia, Karamanli & Ligeris, GR50100 Kozani, Greece
2
Department of Computer Engineering, Technological Educational Institute of Epirus, Kostakioi, GR47100 Arta, Greece
3
Division of Digestive Diseases, Liver Unit, St Mary’s Hospital Campus, Imperial College London, South Wharf Road, W2 1NY London, UK
*
Author to whom correspondence should be addressed.
Academic Editors: José Manuel Ferreira Machado, António Carlos Silva Abelha, Manuel Filipe Vieira Torres dos Santos and Carlos Filipe da Silva Portela
Information 2017, 8(1), 36; https://doi.org/10.3390/info8010036
Received: 31 October 2016 / Revised: 5 March 2017 / Accepted: 14 March 2017 / Published: 20 March 2017
Hepatic steatosis is the accumulation of fat in the hepatic cells and the liver. Triglycerides and other kinds of molecules are included in the lipids. When there is some defect in the process, hepatic steatosis arise, during which the free fatty acids are taken by the liver and exuded as lipoproteins. Alcohol is the main cause of steatosis when excessive amounts are consumed for a long period of time. In many cases, steatosis can lead to inflammation that is mentioned as steatohepatitis or non-alcoholic steatohepatitis (NASH), which can later lead to fibrosis and finally cirrhosis. For automated detection and quantification of hepatic steatosis, a novel two-stage methodology is developed in this study. Initially, the image is processed in order to become more suitable for the detection of fat regions and steatosis quantification. In the second stage, initial candidate image regions are detected, and then they are either validated or discarded based on a series of criteria. The methodology is based on liver biopsy image analysis, and has been tested using 40 liver biopsy images obtained from patients who suffer from hepatitis C. The obtained results indicate that the proposed methodology can accurately assess liver steatosis. View Full-Text
Keywords: hepatic steatosis; fatty liver; liver biopsy image; biopsy image analysis hepatic steatosis; fatty liver; liver biopsy image; biopsy image analysis
Show Figures

Figure 1

MDPI and ACS Style

Tsiplakidou, M.; Tsipouras, M.G.; Giannakeas, N.; Tzallas, A.T.; Manousou, P. Automated Detection of Liver Histopathological Findings Based on Biopsy Image Processing. Information 2017, 8, 36.

AMA Style

Tsiplakidou M, Tsipouras MG, Giannakeas N, Tzallas AT, Manousou P. Automated Detection of Liver Histopathological Findings Based on Biopsy Image Processing. Information. 2017; 8(1):36.

Chicago/Turabian Style

Tsiplakidou, Maria; Tsipouras, Markos G.; Giannakeas, Nikolaos; Tzallas, Alexandros T.; Manousou, Pinelopi. 2017. "Automated Detection of Liver Histopathological Findings Based on Biopsy Image Processing" Information 8, no. 1: 36.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop