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Authors: Delia Mitrea 1 ; Sergiu Nedevschi 1 and Radu Badea 2

Affiliations: 1 Technical University of Cluj-Napoca, Romania ; 2 I. Hatieganu University of Medicine and Pharmacy, Romania

ISBN: 978-989-758-276-9

Keyword(s): Complex Textural Microstructure Co-occurrence Matrices (CTMCM), Textural Model, Hepatocellular Carcinoma, Ultrasound Images, Classification Performance.

Related Ontology Subjects/Areas/Topics: Applications ; Classification ; Computer Vision, Visualization and Computer Graphics ; Feature Selection and Extraction ; Image Understanding ; Medical Imaging ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: The hepatocellular carcinoma is one of the most frequent malignant liver tumours. The golden standard for HCC detection is the needle biopsy, but this is a dangerous technique. We aim to perform the non-invasive recognition of this tumour, using computerized methods within ultrasound images. For this purpose, we defined the textural model of HCC, consisting of the relevant textural features that separate this tumour from other visually similar tissues and of the specific values that correspond to these relevant features: arithmetic mean, standard deviation, probability distribution. In this paper, we demonstrate the role that the Complex Textural Microstructure Co-occurrence Matrices have in the improvement of the textural model of HCC and in the increase of the recognition performance. During the experiments, we considered the following classes: cirrhosis, HCC, cirrhotic parenchyma on which HCC evolved and hemangioma, a frequent benign liver tumour. The resulted recognition accuracy for HCC was towards 90%. (More)

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Paper citation in several formats:
Mitrea, D.; Nedevschi, S. and Badea, R. (2018). Automatic Recognition of the Hepatocellular Carcinoma from Ultrasound Images using Complex Textural Microstructure Co-Occurrence Matrices (CTMCM).In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, pages 178-189. DOI: 10.5220/0006652101780189

@conference{icpram18,
author={Delia Mitrea. and Sergiu Nedevschi. and Radu Badea.},
title={Automatic Recognition of the Hepatocellular Carcinoma from Ultrasound Images using Complex Textural Microstructure Co-Occurrence Matrices (CTMCM)},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={178-189},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006652101780189},
isbn={978-989-758-276-9},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Automatic Recognition of the Hepatocellular Carcinoma from Ultrasound Images using Complex Textural Microstructure Co-Occurrence Matrices (CTMCM)
SN - 978-989-758-276-9
AU - Mitrea, D.
AU - Nedevschi, S.
AU - Badea, R.
PY - 2018
SP - 178
EP - 189
DO - 10.5220/0006652101780189

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