Journal article Open Access

# Brain Tumor Segmentation and Classification using Multiple Feature Extraction and Convolutional Neural Networks

Tasmiya Tazeen; Mrinal Sarvagya

### Citation Style Language JSON Export

{
"DOI": "10.35940/ijeat.F2948.0810621",
"container_title": "International Journal of Engineering and Advanced Technology (IJEAT)",
"language": "eng",
"title": "Brain Tumor Segmentation and Classification using Multiple Feature Extraction and Convolutional Neural Networks",
"issued": {
"date-parts": [
[
2021,
8,
30
]
]
},
"abstract": "<p>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.</p>",
"author": [
{
"family": "Tasmiya Tazeen"
},
{
"family": "Mrinal Sarvagya"
}
],
"page": "23-27",
"volume": "10",
"type": "article-journal",
"issue": "6",
"id": "5408324"
}
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