Hassan Khotanlou

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We propose a new general method for segmenting brain tumors in 3D magnetic resonance images. Our method is applicable to different types of tumors. First, the brain is segmented using a new approach, robust to the presence of tumors. Then a first tumor detection is performed, based on selecting asymmetric areas with respect to the approximate brain symmetry(More)
BACKGROUND Uterine fibroids are common benign tumors of the female pelvis. Uterine artery embolization (UAE) is an effective treatment of symptomatic uterine fibroids by shrinkage of the size of these tumors. Segmentation of the uterine region is essential for an accurate treatment strategy. OBJECTIVES In this paper, we will introduce a new method for(More)
Uterine fibroid is the most common benign tumor of the female in the world. Uterine volume measurement before and after surgery has an important role in predict and following the result of surgery. Fibroids segmentation in patient with multi fibroids is the challenging task manually. We propose tow step method for robustly segmentation of these cases. The(More)
A new method that automatically detects and segments brain tumors in 3D MR images is presented. An initial detection is performed by a fuzzy possibilistic clustering technique and morphological operations, while a deformable model is used to achieve a precise seg-mentation. This method has been successfully applied on five 3D images with tumors of different(More)
This paper introduces a novel methodology for the segmenta-tion of internal brain structures in MRI volumes in the presence of a tumor. The proposed method relies on an initial seg-mentation of the tumor. Based on the tumor's type, a set of spatial relations between internal structures, remaining stable even in presence of the pathology, is established.(More)
Semantic focused crawler computes the priority of pages crawling by web page semantic similarity with topic which is defined by ontology. Ontology is a new approach referred to as the main pivot of change from the present web to a new web called semantic web. The main problem about focused crawlers is to find a computation function of appropriate relevance(More)
This paper introduces a novel methodology for the segmentation of brain MS lesions in MRI volumes using a new clustering algorithm named SCPFCM. SCPFCM uses membership, typicality and spatial information to cluster each voxel. The proposed method relies on an initial segmentation of MS lesions in T1-w and T2-w images by applying SCPFCM algorithm, and the T1(More)
A high quality summary is a main goal and challenge for any automatic text summarization. In this paper, a new method is introduced for automatic text summarization problem. We use cellular learning automata for calculating similarity of sentences, particle swarm optimization method for weighting to the features according to their importance and use fuzzy(More)
Today, enterprises consider their produced and existing knowledge a principal capital and seek to collect and maintain this knowledge. Unfortunately, the bulk of the enterprises' implicit knowledge has been gradually faded or neglected, due to lack of necessary attention and suitable saving. In this paper we attempt to present an efficient methodology based(More)