We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). Standard Deviation, Mean, Energy and Entropy are extorted using the histogram approach for each merger space. These features are found to be higher in occurrence in the tumor region than the non-tumor one. MRI scans of the five brains with 60 slices from each are utilized for testing the proposed method’s authenticity. These brain images (230 slices as normal and 70 abnormal) are accessed from the Internet Brain Segmentation Repository (IBSR) dataset. 60% images for training and 40% for testing phase are used. Average classification accuracy as much as 98.02% (training) and 98.19% (testing) are achieved.
The magnetic properties of a pure Nickel metal and Nickel-Zinc-Manganese ferrites having the chemical formula Ni0.1(Zn0.4Mn0.6)0.9Fe2O4 were studied. The phase formation and crystal structure was studied by using x-ray diffraction which confirmed the formation of pure single spinel cubic phase with space group (Fd3m) in the ferrite. The samples microstructure was studied with scanning electron microstructure and EDX. The magnetic properties of the ferrite and nickel metal were characterized by using a laboratory setup with a magnetic field in the range from 0-500 G. The ferrite showed perfect soft spinel phase behavior while the nickel sample showed higher magnetic loss an
... Show MoreAlthough the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t
... Show MoreRA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
Background: Recent advancements in molecular techniques have identified over 450 genotypes of Human Papillomavirus (HPV), classified into low- and high-oncogenic risk categories. The rise in high-oncogenic risk HPV genotypes has been linked to various cancers, including those affecting the oral, oropharyngeal, and nasopharyngeal regions in both pediatric and adult populations. Methods: In this study, a cohort of 102 tonsillar tissue samples was included. This comprised 40 specimens from pediatric patients aged 4 to 9 years with nasopharyngeal adenoid hypertrophies, and 42 specimens from pediatric patients aged 5 to 12 years with palatine tonsillar hypertrophies. Among the 82 tonsillar tissue samples analyzed, 38 were from pediatric patients
... Show MoreThe emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t
... Show MoreThe internet, unlike other traditional means of communication, has a flexibility to stimulate the user and allows him to develop it. Perhaps, the reason for the superiority of the internet over other traditional means of communication is the possibility of change and transmission from one stage to another in a short period. This means that the internet is able to move from the use to the development of the use and then the development of means and innovation as the innovation of the internet is a logical product of the interaction of the user with the network. The internet invests all the proposals and ideas and does not ignore any even if it is simple. This is represented in social networking sites which in fact reflects personal emotio
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