August 30, 2021 Journal article Open Access

Tasmiya Tazeen; Mrinal Sarvagya

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{
  "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"
}