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Kalifa Shantta,Otman Basir
Pág. 55 - 61
Even with the enormous progress in medical technology, brain tumor detection is still an extremely tedious and complex task for the physicians. The early and accurate detection of brain tumors enables effective and efficient therapy and thus can result i...
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Wandile Nhlapho, Marcellin Atemkeng, Yusuf Brima and Jean-Claude Ndogmo
The advent of deep learning (DL) has revolutionized medical imaging, offering unprecedented avenues for accurate disease classification and diagnosis. DL models have shown remarkable promise for classifying brain tumors from Magnetic Resonance Imaging (M...
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Dimitrios Kollias, Karanjot Vendal, Priyankaben Gadhavi and Solomon Russom
Brain tumors pose significant health challenges worldwide, with glioblastoma being one of the most aggressive forms. The accurate determination of the O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status is crucial for personalized t...
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Manar Ahmed Hamza, Hanan Abdullah Mengash, Saud S. Alotaibi, Siwar Ben Haj Hassine, Ayman Yafoz, Fahd Althukair, Mahmoud Othman and Radwa Marzouk
A brain tumor (BT) is an abnormal development of brain cells that causes damage to the nerves and blood vessels. An accurate and early diagnosis of BT is important to prevent future complications. Precise segmentation of the BT provides a basis for surgi...
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Fabio Cumbo, Eleonora Cappelli and Emanuel Weitschek
The recent advancements in cancer genomics have put under the spotlight DNA methylation, a genetic modification that regulates the functioning of the genome and whose modifications have an important role in tumorigenesis and tumor-suppression. Because of...
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Norah Fahd Alhussainan, Belgacem Ben Youssef and Mohamed Maher Ben Ismail
Brain tumor diagnosis traditionally relies on the manual examination of magnetic resonance images (MRIs), a process that is prone to human error and is also time consuming. Recent advancements leverage machine learning models to categorize tumors, such a...
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Ayesha Younis, Li Qiang, Charles Okanda Nyatega, Mohammed Jajere Adamu and Halima Bello Kawuwa
A brain tumor is a distorted tissue wherein cells replicate rapidly and indefinitely, with no control over tumor growth. Deep learning has been argued to have the potential to overcome the challenges associated with detecting and intervening in brain tum...
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Rahmeh Ibrahim, Rawan Ghnemat and Qasem Abu Al-Haija
Convolutional Neural Networks (CNNs) have exhibited remarkable potential in effectively tackling the intricate task of classifying MRI images, specifically in Alzheimer?s disease detection and brain tumor identification. While CNNs optimize their paramet...
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Sami Bourouis, Roobaea Alroobaea, Saeed Rubaiee and Anas Ahmed
Accurate medical images analysis plays a vital role for several clinical applications. Nevertheless, the immense and complex data volume to be processed make difficult the design of effective algorithms. The first aim of this paper is to examine this are...
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Sarfaraz Natha, Umme Laila, Ibrahim Ahmed Gashim, Khalid Mahboob, Muhammad Noman Saeed and Khaled Mohammed Noaman
Brain tumors (BT) represent a severe and potentially life-threatening cancer. Failing to promptly diagnose these tumors can significantly shorten a person?s life. Therefore, early and accurate detection of brain tumors is essential, allowing for appropri...
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Milica M. Bad?a and Marko C. Barjaktarovic
The use of machine learning algorithms and modern technologies for automatic segmentation of brain tissue increases in everyday clinical diagnostics. One of the most commonly used machine learning algorithms for image processing is convolutional neural n...
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