Khalifa Djemal

Learn More
To limit the noise in an image, some techniques are based on the calculation of an average intensity in each pixel of the image by considering a some neighbor. However, these techniques tend to attenuate contours present in the image. This affect edge and particularly penalizing for the segmentation algorithms whose finality is to find contours. The(More)
We present an automatic technique for contour detection of the abdominal aorta on a medical images sequence. We apply the method of region based active contours using local parameter estimation related to the object region. This method allows the automation of the detection process. The initialization of our algorithm is only done on the first image of the(More)
Received Revised Accepted In this paper we present a new algorithm to track an organ in a sequence of medical images in order to achieve a 3D reconstruction. The automatic method that we propose allows the tracking of the external contour of the anatomical organ in all the sequence from one contour initialized by the user on the first image. The required(More)
Many pattern recognition and machine learning methods have been used in cancer diagnosis. The Artificial Immune System (AIS) is a novel computational intelligence technique. Designed by the principles of the natural immune system, it is able of learning, memorize and perform pattern recognition. The AIS's are used in various domains as intrusion detection,(More)
Noise reduction is a very important task in image processing. In this aim, many approaches and methods have been developed and proposed in the literature. In this paper, we present a new restoration method for noisy images by minimizing the Total Variation (TV) under constraints using a multilayer neural network (MLP). Indeed, the obtained Euler-Lagrange(More)
Content-based image retrieval (CBIR) techniques are becoming increasingly important in various fields. One of the most important steps in CBIR systems is feature extraction. However, using not appropriate features in heterogeneous image database during retrieval process does not provide a complete description of an image. Indeed, each feature is able to(More)
In this work, a hybrid classification system based local database categorization is proposed for breast cancer classification. The proposed approach aims to improve the classification rate of the Artificial Immune System (AIS) and reduce its computational time. The principle of the hybrid classifier based AIS consists in categorizing the cells sets in(More)