Thyroid is a small butterfly shaped gland located in the front of the neck just below the Adams apple. Thyroid is one of the endocrine gland, which produces hormones that help the body to control metabolism. A different thyroid disorder includes Hyperthyroidism, Hypothyroidism, and thyroid nodules (benign/malignant). Ultrasound imaging is most commonly used to detect and classify abnormalities of the thyroid gland. Segmentation method is a tool that used widely in many applications including medical image processing. One of the common applications of segmentation is in medical image analysis for clinical diagnosis that has an important role in terms of quality and quantity.
The main objective of this research is to use the Computer-Ai

Automatic Speaker Profiling (ASP), is concerned with estimating the physical traits of a person from their voice. These traits include gender, age, ethnicity, and physical parameters. Reliable ASP has a wide range of applications such as mobile shopping, customer service, robotics, forensics, security, and surveillance systems.  Research in ASP has gained interest in the last decade, however, it was focused on different tasks individually, such as age, height, or gender. In this work, a review of existing studies on different tasks of speaker profiling is performed. These tasks include age estimation and classification, gender detection, height, and weight estimation This study aims to provide insight into the work of ASP, available dat

Background: image processing of medical images is major method to increase reliability of cancer diagnosis.
Methods: The proposed system proceeded into two stages: First, enhancement stage which was performed using of median filter to reduce the noise and artifacts that present in a CT image of a human lung with a cancer, Second: implementation of k-means clustering algorithm.
Results: the result image of k-means algorithm compared with the image resulted from implementation of fuzzy c-means (FCM) algorithm.
Conclusion: We found that the time required for k-means algorithm implementation is less than that of FCM algorithm.MATLAB package (version 7.3) was used in writing the programming code of our w

    Image segmentation is a basic image processing technique that is primarily used for finding segments that form the entire image. These segments can be then utilized in discriminative feature extraction, image retrieval, and pattern recognition. Clustering and region growing techniques are the commonly used image segmentation methods. K-Means is a heavily used clustering technique due to its simplicity and low computational cost. However, K-Means results depend on the initial centres’ values which are selected randomly, which leads to inconsistency in the image segmentation results. In addition, the quality of the isolated regions depends on the homogeneity of the resulted segments. In this paper, an improved K-Means

It is not often  easy to identify a certain group of words as a lexical bundle, since the same set of words can be, in different situations, recognized as idiom,  a collocation, a lexical phrase or a lexical bundle. That is, there are many cases where the overlap among the four types is plausible. Thus, it is important to extract the most identifiable and distinguishable characteristics with which a certain group of words, under certain conditions, can be recognized as a lexical bundle, and this is the task of this paper.

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

The city of Derna has distinctive architectural and architectural features, like other Arab and Islamic cities in the Arab West and North Africa. Its markets and shops have taken many different forms and structural forms within the urban fabric of the central commercial zone. The meeting between the various commercial and handicraft jobs and consumers within a spatial area starting with the old markets of the dark market and the agency of the harvest and vegetable market and the mosque of the old and the square of the mosque and the Red Square and the square Kharazin. It then grew linearly towards commercial hubs that were associated with the city's expansion axes. Old markets represent the architectural and planning heritage associated

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati