Prostate cancer is the commonest male cancer and the second leading cause of cancer-related death in men. Over many decades, prostate cancer detection represented a continuous challenge to urologists. Although all urologists and pathologists agree that tissue diagnosis is essential especially before commencing active surgical or radiation treatment, the best way to obtain the biopsy was always the big hurdle. The heterogenicity of the tumor pathology is very well seen in its radiological appearance. Ultrasound has been proven to be of limited sensitivity and specificity in detecting prostate cancer. However, it was the only available targeting technique for years and was used to guide biopsy needle passed transrectally or transperineally. Magnetic Resonance Imaging (MRI) has revolutionized the process with the advent of its multiparametric imaging (mp MRI) where the prostate is evaluated by different MRI techniques and the likelihood of the detected lesion is scored using the new prostate imaging-reporting and data system (PIRADS) scoring. Despite the improved detection of clinically significant prostate cancer by mpMRI, the ideal way to target the area of suspicion detected by mpMRI is the next level of challenge. In this review article, we will discuss the recent methods of targeting and focus on the different platforms used to integrate the mpMRI static images with the real-time US scanning in what is called (US-MRI fusion techniques).
In a world of fierce competition companies of different activities strive to strengthen their competitiveness in order to be able to deliver greater value to their customers and gain a distinct sites in competition with other companies in the market at the local and international levels. Every company seeks to focus on one or more of the competitive capabilities in order to turn it into an obvious advantage or a number of competitive advantages to contribute in improving the performance and superiority over its competitors. Therefore, the management of companies no longer need only useful information for the internal aspects of the environment, but also need to include the external environment that includes various and constantly changin
... Show MoreConsistent with developments emerging environmental and canaccept by Iraq of the opportunities and challenges ahead in many fields,including economic areas, it requires the face of those developments andadaptation by adopting a lot of related concepts, including the concept ofcorporate governance and commitment to its principles, standards andmechanisms, especially those related to the formation of audit committeesand identify the tasks and duties entrusted to its members and terms oftheir independence as well as the rehabilitation of both scientific andpractical manner that is consistent with the interests of shareholders andother stakeholders in the companies, including banks, research sample, theresearch aims to shed light on the conc
... Show MoreAn essential tool for studying the web is its ability to show how energy moves through an ecosystem. Understanding and elucidating the relationship between species variety and their placement within the inclusive trophic dynamics is also beneficial. A food web ecological model with prey and two rival predators under fear and wind flow conditions is developed in this article. The boundedness and positivity of the system’s solution are established mathematically. The stability and existence constraints of the system’s equilibria are examined. The proposed system’s persistence limitations are established. Additionally, the bifurcation analysis of every potential equilibrium is examined using the Sotomayor theorem. To describe the
... Show MoreDetermining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreDeepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp
... Show MoreWith the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative
... Show MoreSeveral Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff
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