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An real and accurate brain diagnosis process on mri brain images using enr machine learning
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| Author:
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SRINIVASARAO GAJULA, V. RAJESH
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| Abstract:
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In this research, brain-related diseases are detected on MRI brain images for real and correct disease diagnosis. Brain diseases are very dangerous to, and may even be caused by human health conditions; the normal actions of parts of the body can begin to die. Many experts have implemented multiple monitoring mechanisms for brain abnormalities, but they remain constrained in terms of accessibility and forms of diseases. Improvement is also necessary in terms of rapid diagnosis and detection of brain disorders. This research work consisted predominantly of three types of recognition method for brain diseases, which are ALZHEIMER'S, Transient Ischemic Attack (TIA) and Tumors. Real-time brain MRI images are obtained for analysis of numerous orientations and diverse age ranges. Two measures, such as logistic regression (ENR) and threshold segmentation, are applied to selected images for diagnosis and detection. This TSENR paradigm is further improved and competes with new technology..
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| Keyword:
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MRI brain image, ENR machine learning algorithm, threshold segmentation.
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.04.549
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| Download:
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Request For Article
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