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  • Open Access

    ARTICLE

    Computer-Aided Diagnosis Model Using Machine Learning for Brain Tumor Detection and Classification

    M. Uvaneshwari1, M. Baskar2,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1811-1826, 2023, DOI:10.32604/csse.2023.035455

    Abstract The Brain Tumor (BT) is created by an uncontrollable rise of anomalous cells in brain tissue, and it consists of 2 types of cancers they are malignant and benign tumors. The benevolent BT does not affect the neighbouring healthy and normal tissue; however, the malignant could affect the adjacent brain tissues, which results in death. Initial recognition of BT is highly significant to protecting the patient’s life. Generally, the BT can be identified through the magnetic resonance imaging (MRI) scanning technique. But the radiotherapists are not offering effective tumor segmentation in MRI images because of the position and unequal shape… More >

  • Open Access

    ARTICLE

    Segmentation of Brain Tumor Magnetic Resonance Images Using a Teaching-Learning Optimization Algorithm

    J. Jayanthi1,*, M. Kavitha2, T. Jayasankar3, A. Sagai Francis Britto4, N. B. Prakash5, Mohamed Yacin Sikkandar6, C. Bharathiraja7

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4191-4203, 2021, DOI:10.32604/cmc.2021.012252

    Abstract Image recognition is considered to be the pre-eminent paradigm for the automatic detection of tumor diseases in this era. Among various cancers identified so far, glioma, a type of brain tumor, is one of the deadliest cancers, and it remains challenging to the medicinal world. The only consoling factor is that the survival rate of the patient is increased by remarkable percentage with the early diagnosis of the disease. Early diagnosis is attempted to be accomplished with the changes observed in the images of suspected parts of the brain captured in specific interval of time. From the captured image, the… More >

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