Belgherbi. Aicha

Work place: Biomedical engineering laboratory, Electrical and Electronics engineering Department Tlemcen University, 13000, Algeria.

E-mail: mmebelladgham@yahoo.fr

Website:

Research Interests: Medical Image Computing, Image Processing, Image Manipulation

Biography

Belgherbi. Aicha received the Diploma Engineering degree from the Tlemcen University of Technology in 2005. She interest in medical image processing. She had obtained its master degree diploma in biomedical image processing in 2009 from the Tlemcen University of Technology. From 2009 until 2012 she works as a researcher in Electrical and Electronics engineering Department of Tlemcen University. Currently, she is in third year Ph.D student in biomedical engineering at the University of Tlemcen –Algeria. Here research focuses on mathematical morphology application to the biomedical image processing. From 2010 until 2012, she was a member of national research project NRP. From 2010 until 2011, 2011-2012, she was a member of tutored system; she gives courses in biomedical signal processing and numerical method

Author Articles
Morphological Segmentation of the Spleen From Abdominal CT Images

By Belgherbi. Aicha Bessaid Abdelhafid

DOI: https://doi.org/10.5815/ijigsp.2012.04.08, Pub. Date: 8 May 2012

Organ segmentation is an important step in various medical image applications. Accurate spleen segmentation in abdominal CT images is one of the most important steps for computer aided spleen pathology diagnosis. In this paper, we have proposed a new semi-automatic algorithm for spleen area extraction in abdominal CT images. The algorithm contains several stages. A spleen segmentation method is based on watershed approach. The first, we seek to determine the region of interest by applying the morphological filters such as the geodesic reconstruction to extract the spleen. Secondly, a pre-processing method is employed. In this step, we propose a method for improving the image gradient by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the spleen segmentation by the watershed transform controlled by markers. The new segmentation technique has been evaluated on different CT images, by comparing the semi-automatically detected spleen contour to the spleen boundaries manually traced by an expert. The experimental results are described in the last part in this work. The automated method provides a sensitivity of 95% with specificity of 99% and performs better than other related methods.

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