Diagnosis System for Hepatocellular Carcinoma Based on Fractal Dimension of Morphometric Elements Integrated in an Artificial Neural Network
Joint Authors
Streba, Letiția Adela Maria
Gheonea, Dan Ionuț
Comănescu, Maria
Streba, Costin Teodor
Pirici, Daniel
Șerbănescu, Mircea
Rogoveanu, Ion
Mogoantă, Stelian
Vere, Cristin Constantin
Ciurea, Marius Eugen
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-16
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Background and Aims.
Hepatocellular carcinoma (HCC) remains a leading cause of death by cancer worldwide.
Computerized diagnosis systems relying on novel imaging markers gained significant importance in recent years.
Our aim was to integrate a novel morphometric measurement—the fractal dimension (FD)—into an artificial neural network (ANN) designed to diagnose HCC.
Material and Methods.
The study included 21 HCC and 28 liver metastases (LM) patients scheduled for surgery.
We performed hematoxylin staining for cell nuclei and CD31/34 immunostaining for vascular elements.
We captured digital images and used an in-house application to segment elements of interest; FDs were calculated and fed to an ANN which classified them as malignant or benign, further identifying HCC and LM cases.
Results.
User intervention corrected segmentation errors and fractal dimensions were calculated.
ANNs correctly classified 947/1050 HCC images (90.2%), 1021/1050 normal tissue images (97.23%), 1215/1400 LM (86.78%), and 1372/1400 normal tissues (98%).
We obtained excellent interobserver agreement between human operators and the system.
Conclusion.
We successfully implemented FD as a morphometric marker in a decision system, an ensemble of ANNs designed to differentiate histological images of normal parenchyma from malignancy and classify HCCs and LMs.
American Psychological Association (APA)
Gheonea, Dan Ionuț& Streba, Costin Teodor& Vere, Cristin Constantin& Șerbănescu, Mircea& Pirici, Daniel& Comănescu, Maria…[et al.]. 2014. Diagnosis System for Hepatocellular Carcinoma Based on Fractal Dimension of Morphometric Elements Integrated in an Artificial Neural Network. BioMed Research International،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-456485
Modern Language Association (MLA)
Gheonea, Dan Ionuț…[et al.]. Diagnosis System for Hepatocellular Carcinoma Based on Fractal Dimension of Morphometric Elements Integrated in an Artificial Neural Network. BioMed Research International No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-456485
American Medical Association (AMA)
Gheonea, Dan Ionuț& Streba, Costin Teodor& Vere, Cristin Constantin& Șerbănescu, Mircea& Pirici, Daniel& Comănescu, Maria…[et al.]. Diagnosis System for Hepatocellular Carcinoma Based on Fractal Dimension of Morphometric Elements Integrated in an Artificial Neural Network. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-456485
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-456485