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All Journal Jurnal Informatika Upgris International Journal of Research and Applied Technology (INJURATECH) Bulletin of Social Informatics Theory and Application The Indonesian Journal of Computer Science
askar, shavan
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Social Sciences

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A comparative evaluation for Detection Brain Tumor in MRI Image using Machine learning algorithms Kareem, Shahab; askar, shavan; Abdulkhaleq, Ibrahim; Hawezi, Roojwan Sc.
Jurnal Informatika UPGRIS Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.9503

Abstract

In medical imaging, automated defect identification of defects has taken on a prominent position. Unaided prediction of tumor (brain) recognition in magnetic resonance imaging process (MRI) is vital for patient preparation. With traditional methods of identifying z is designed to reduce the burden on radiologists. One of the problems with MRI brain tumor diagnosis is the size and variation of their molecular structures. This article uses deep learning techniques (Artificial neural network ANN, Naive Bayes NB, Multi-layer Perceptron MLP ) to discover brain tumors in the MRI scans. First, the brain MRI images are run through the preprocessing steps to remove texture features. Next, these features are used to train a machine learning algorithm.
Co-Authors Abdulkhaleq, Ibrahim Abdullah, Nihad Abdullah, Rebwar Abdulwahab, Sara Ahmed Al-Zakhali, Omar Ahmed, Kosrat Dlshad Ahmed, Mariwan Ali, Daban Aziz Mohammed, Marwan Bilal, Noura Hamad, Soran Hawezi, Roojwan Sc. Hussein, Diana Hussien, Diana Ibrahim, Media Ibrahim, Media Ali Kareem, Shahab Kareem, Shahab Wahhab Khosnawi, Dilshad Maghdid, Souzan Maghdid, Sozan Mohammed , Marwan Aziz Mohammed, Mariwan Muheden, Karwan Omer, Saman M. Othman, Mina Saeed, Hasan Saleem, Mohammad saleem, mohammed Sami Khoshaba, Farah Soran, Zhala Zeebaree, Subhi