Heart region extraction and segmentation from chest CT images using Hopfield Artificial Neural Networks

Author

Sammouda, Rachid ; Jomaa, Rami Mohammad ; Mathkour, Hassan

Author_Institution

Dept. of Comput. Sci., King Saud Univ. Riyadh, Riyadh, Saudi Arabia

fYear

2012

fDate

24-26 March 2012

Firstpage

1

Lastpage

6

Abstract

A system for extracting and segmenting heart regions from three-dimensional (3D) CT chest images is proposed in this paper. At first, the regions of interest (ROIs) are extracted using pure basic image processing techniques applied on the 2D CT slices. Secondly, the ROIs in each slice are segmented using Hopfield Artificial Neural Networks (HANN). The segmentation results include tissues belonging to the heart and its surrounding organs. To distinguish between heart regions and the non-heart regions, a rule-based filtering approach is adopted. The system is evaluated using a database of 735 chest CT slices from 5 patients. It shows a good and accurate performance with some exceptions.

Keywords

Hopfield neural nets; biological tissues; cardiology; computerised tomography; feature extraction; filtering theory; image segmentation; medical image processing; 2D CT slices; 3D chest CT images; HANN; Hopfield artificial neural networks; ROI; heart region extraction; heart region segmentation; image processing techniques; regions of interest; rule-based filtering approach; three-dimensional CT chest images; tissues; Artificial neural networks; Biomedical imaging; Computed tomography; Feature extraction; Filtering; Heart; Image segmentation; 3D Chest CT images; Heart Region Extraction; Hopfiel Neural Networks; Segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology and e-Services (ICITeS), 2012 International Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4673-1167-0

Type

conf

DOI

10.1109/ICITeS.2012.6216678

Filename

6216678