August 30, 2021 Journal article Open Access

Tasmiya Tazeen; Mrinal Sarvagya

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    <subfield code="a">Segmentation, Brain Tumor, Convolutional  Neural Network, Deep Learning.</subfield>
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    <subfield code="a">Brain Tumor Segmentation and Classification using Multiple Feature Extraction and Convolutional Neural Networks</subfield>
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    <subfield code="a">&lt;p&gt;Intracranial tumors are a type of cancer that grows spontaneously inside the skull. Brain tumor is the cause for one in four deaths. Hence early detection of the tumor is important. For this aim, a variety of segmentation techniques are available. The fundamental disadvantage of present approaches is their low segmentation accuracy. With the help of magnetic resonance imaging (MRI), a preventive medical step of early detection and evaluation of brain tumor is done. Magnetic resonance imaging (MRI) offers detailed information on human delicate tissue, which aids in the diagnosis of a brain tumor. The proposed method in this paper is Brain Tumour Detection and Classification based on Ensembled Feature extraction and classification using CNN.&lt;/p&gt;</subfield>
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