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    Intelligent Brain Tumor Detector

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    Date
    2023-01-01
    Author
    Abdelhamid, Mostafa
    Alhato, Mohammed
    Elmancy, Ali
    Al-Maadeed, Somaya
    El Harrouss, Omar
    Metadata
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    Abstract
    A major challenge in brain tumor treatment planning is determination of the tumor extent. Brain tumor disease can be identified with imaging techniques such as MRI. The images produced by an MRI scan can provide a clear view of the brain's internal structures, including the presence of any abnormal growths or tumors. Tumors can be seen on the images as areas of abnormal tissue that have a different signal intensity from normal brain tissue. In addition, the MRI images can also provide information about the size, shape, location, and characteristics of the tumor, such as its blood flow and whether it is solid or cystic. This information can be very helpful in determining the best course of treatment for the patient. The main objective of this paper is to recognize the existence of tumors in the brain from MRI images using machine learning techniques. Our results show that the k-nearest approach is capable of precisely identifying brain cancers with more than 97%.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85179846020&origin=inward
    DOI/handle
    http://dx.doi.org/10.1109/ISNCC58260.2023.10323954
    http://hdl.handle.net/10576/60098
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    • Computer Science & Engineering [‎2428‎ items ]

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