40 Int. J. Applied Pattern Recognition, Vol. 5, No. 1, 2018 Copyright © 2018 Inderscience Enterprises Ltd. New semi-automated segmentation approach of the left ventricle applied to cine MR images analysis Mahammed Messadi*, Abdelhafid Bessaid and Sihem Lazzouni Biomedical Engineering Laboratory GBM, Tlemcen University, Algeria Email: m_messadi@yahoo.fr Email: a.bessaid@gmail.com Email: sa_lazzouni@yahoo.fr *Corresponding author Abstract: Cardiovascular abnormalities have become one of the most dangerous diseases. They affect people around the entire world and some countries are more concerned by this illness. In this paper, a new methodological approach dedicated to analyse and delineate the short-axis cardiac MRI of the left ventricle (LV) is presented. In this case, thresholding and morphological operation, active contours model and region growing are combined to extract endocardial exactly. The systole volume (VTS), diastole volume (VTD) and ejection volume (EV) are then successively calculated to predict the cardiovascular diseases. The results are validated by a database (Cousty et al., 2010) where the expert manual contouring was available and the similarity index (Jaccard index) between the proposed method and expert segmentations are calculated. After discussion, we conclude that the presented method leads to satisfying results end-diastolic endocardium (0.92) and end- systolic endocardium (0.88), achieving both fast calculation and accuracy objectives. Keywords: cardiac MRI image; left ventricle; active contour; border detection; region growing; ejection volume; comparison. Reference to this paper should be made as follows: Messadi, M., Bessaid, A. and Lazzouni, S. (2018) ‘New semi-automated segmentation approach of the left ventricle applied to cine MR images analysis’, Int. J. Applied Pattern Recognition, Vol. 5, No. 1, pp.40–54. Biographical notes: Mahammed Messadi is an Assistant Professor at the Tlemcen University, Algeria. She received her Engineering degree in Electrical from the Tlemcen University in 2003. In 2010, she obtained her PhD in Biomedical Engineering from the University of Tlemcen, Algeria. Her research interests are in computer vision, computational intelligence (CI), image processing, neural networks and clustering methods. Abdelhafid Bessaid is a Professor at the Tlemcen University, Algeria. He received his Engineering degree in Electrical from the Belabess University in 1997. In 2003, he obtained his PhD in Electrical from the University of Belabess, Algeria. He is currently a Professor at the Tlemcen University, Algeria, and Head of Medical Image (IM) research team at the Biomedical. He conducted post-doctoral teaching and research at the University of Tlemcen. His is a member of several scientific conferences. His research interests have been in image processing and artificial intelligence.