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Knowledge of left atrial (LA) anatomy is important for atrial fibrillation ablation guidance, fibrosis quantification and biophysical modelling. Segmentation of the LA from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images is a complex problem. This manuscript presents a benchmark to evaluate algorithms that address LA segmentation. The(More)
Web services are becoming the most important paradigm for distributed computing and electronic business. They are self-contained Internet accessible applications that are capable not only of performing business activities on their own, but they also possess the ability to engage with other Web services in order to build new value-added services. In this(More)
The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K-(More)
The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System 2 (AIRS2) is one of the methods used in medical classification problems. In this paper, we used a Modified AIRS2 (MAIRS2) where we replace the Knearest neighbors algorithm with the fuzzy K-nearest(More)
Segmentation of the left ventricle in MRI images is a task with important diagnostic power. Currently, the evaluation of cardiac function involves the global measurement of volumes and ejection fraction. This evaluation requires the segmentation of the left ventricle contour. In this paper, we propose a new method for automatic detection of the endocardial(More)
In the context of arabic Information Retrieval Systems (IRS) guided by arabic ontology and to enable those systems to better respond to user requirements, this paper aims to representing documents and queries by the best concepts extracted from Arabic Wordnet. Identified concepts belonging to Arabic WordNet synsets are extracted from documents and queries,(More)
This paper presents a fuzzy rule based classifier and its application to discriminate premature ventricular contraction (PVC) beats from normals. An Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied to discover the fuzzy rules in order to determine the correct class of a given input beat. The main goal of our approach is to create an interpretable(More)
The segmentation of microscopic images is an important issue in biomedical image processing. Many works can be found in the literature; however, there is not a gold standard method that is able to provide good results for all kinds of microscopic images. Then, authors propose methods for a given kind of microscopic images. This paper deals with new(More)
In this paper, we present the methods that we have proposed and used in the liver image annotation task of ImageCLEF 2015.This challenge entailed the annotation of liver CT scans to generate a structured report. To meet this challenge we have proposed two methods for annotating the liver image. The first one uses a classification approach, which is composed(More)