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.
With the freedom offered by the Deep Web, people have the opportunity to express themselves freely and discretely, and sadly, this is one of the reasons why people carry out illicit activities there. In this work, a novel dataset for Dark Web active domains known as crawler-DB is presented. To build the crawler-DB, the Onion Routing Network (Tor) was sampled, and then a web crawler capable of crawling into links was built. The link addresses that are gathered by the crawler are then classified automatically into five classes. The algorithm built in this study demonstrated good performance as it achieved an accuracy of 85%. A popular text representation method was used with the proposed crawler-DB crossed by two different supervise
... Show MoreSuicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o
... Show MoreBackground: Morphology of the root canal system is divergent and unpredictable, and rather linked to clinical complications, which directly affect the treatment outcome. This objective necessitates continuous informative update of the effective clinical and laboratory methods for identifying this anatomy, and classification systems suitable for communication and interpretation in different situations. Data: Only electronic published papers were searched within this review. Sources: “PubMed” website was the only source used to search for data by using the following keywords "root", "canal", "morphology", "classification". Study selection: 153 most relevant papers to the topic were selected, especially the original articles and review pa
... Show MoreAlopecia (Baldness) is very usual trouble in current time. It is accompanied by an intensive weakening of the scalp's hair and follows a specific pattern. Hereditary predisposition plays a very important role in alopecia despite not completely understood. Alopecia can be typed to various categories according to etiology, may be due to hereditary factors, autoimmune disease, and drugs or chemicals. There are many options of strategies of treatment according to the type and causes of alopecia. Chemical or synthetic medications apply for the management of hair loss are accompanied by a wide range of undesirable effects. Naturally occurring drugs also play important role in alopecia management with minimal side effects.
Iris recognition occupies an important rank among the biometric types of approaches as a result of its accuracy and efficiency. The aim of this paper is to suggest a developed system for iris identification based on the fusion of scale invariant feature transforms (SIFT) along with local binary patterns of features extraction. Several steps have been applied. Firstly, any image type was converted to grayscale. Secondly, localization of the iris was achieved using circular Hough transform. Thirdly, the normalization to convert the polar value to Cartesian using Daugman’s rubber sheet models, followed by histogram equalization to enhance the iris region. Finally, the features were extracted by utilizing the scale invariant feature
... Show MoreThe science of jurisprudence is one of the legal sciences that scholars have been interested in since the first centuries of Islam, and they wrote many books about it, and the science of manuscripts is considered one of the scientific achievements in which many scholars emerged, including Imam Al-Samaani, so I chose this manuscript related to Istism to clarify its concept and meaning for all people, The student (Ali Ahmed Abdel-Aziz Sheikh Hamad) preceded me in the investigation of part of the book, and it was facilitated for me, by the grace of God Almighty, to investigate the issue (if one of the Muslim spouses apostatized and one of the infidel spouses converted to Islam until the end of the issue of if the two spouses were taken capt
... Show More—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb
... Show MoreRecently digital mammography is most widely used technology for early detection of breast cancer. The main diagnosing elements such as lesion or masses in digital mammograms are with law contrast. The purpose of this paper is to enhance the mammogram images by increasing its contrast. Different enhancement method are used for this purpose such as histogram equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Morphological, and Retinex. The Retinex method also implement by combining it with HE once, and with CLAHE to improve its performance. The experimental results show that using Retinex with CLAHE can produce an image with enhancement in contrast better than using it with HE method and better than other methods
... Show MoreNowadays, the rapid development of multi-media technology and digital images transmission by the Internet leads the digital images to be exposed to several attacks in the transmission process. Therefore, protection of digital images become increasingly important.
To this end, an image encryption method that adopts Rivest Cipher (RC4) and Deoxyribonucleic Acid (DNA) encoding to increase the secrecy and randomness of the image without affecting its quality is proposed. The Means Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Coefficient Correlation (CC) and histogram analysis are used as an evaluation metrics to evaluate the performance of the proposed method. The results indicate that the proposed method is secure ag
... Show MoreSkull 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
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