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ENHANCED COMPUTERIZED BRAIN TUMOR DETECTION SYSTEM USING EFFICIENT MRI BASED IMAGE FILTERING TECHNIQUE.

Brain tumors are the outcome of unusual growths and uncontrolled cells splitting in the brain. If the diagnosis of the brain tumor should be done early with high accuracy, else the treatment will be much difficult or sometimes it may lead to death. Certain sorts of brain tumor like Meningioma, Gliom...

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Published in:Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 2102 - 2108
Main Authors: S., PALANIVEL RAJAN, T., DHARSHINI, D., PRIYADHARSINI, M., VARSHA
Format: diagnostic images tables/charts Journal Article
Published: Turkish Journal of Physiotherapy & Rehabilitation 2021
Online Access:View this record in EBSCOhost
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      issn: 13008757
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      dt: 2021
      vid: 32
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      pub: Turkish Journal of Physiotherapy & Rehabilitation
      place: Kizilay/ Ankara, <Blank>
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      tig:
        atl: ENHANCED COMPUTERIZED BRAIN TUMOR DETECTION SYSTEM USING EFFICIENT MRI BASED IMAGE FILTERING TECHNIQUE.
      aug:
        au:
          S., PALANIVEL RAJAN
          T., DHARSHINI
          D., PRIYADHARSINI
          M., VARSHA
        affil: Associate Professor, Department of Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur, Tamilnadu, India
      sug:
        subj:
          Brain Neoplasms Diagnosis
          Magnetic Resonance Imaging Methods
          Image Processing, Computer Assisted
          Predictive Value of Tests
          Deep Learning
          Neural Networks (Computer)
          Image Interpretation, Computer Assisted
          Image Enhancement Methods
          Probability
      ab: Brain tumors are the outcome of unusual growths and uncontrolled cells splitting in the brain. If the diagnosis of the brain tumor should be done early with high accuracy, else the treatment will be much difficult or sometimes it may lead to death. Certain sorts of brain tumor like Meningioma, Glioma, and Pituitary tumors are more usual than the others. Magnetic Resonance Imaging (MRI) is a form of medical imaging that uses magnetic fields to produce images, which is widely used for identification and treatment of brain tumors in clinical practice. The photographs of Magnetic Resonance are drawn from three different perspectives. Sagittal, axial, and coronal views are the three types. The most complicated aspect of detecting a brain tumor is segmenting it. The pattern of Brain tumor is detected by using Deep Learning techniques to overcome the human error or mistakes in manual segmentation. In this project, we can use a range of image processing techniques, such as grayscale conversion and attribute extraction using Grey level Co-occurrence. By using Neural Network Algorithm like Convolution Neural Network (CNN), the ultimate classification process concludes whether the person is diseased or not. Experimental result shows that the proposed CNN can be outperforms than the existing machine learning algorithms.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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