Cite this DOI

H BHAGYA LAKSHMI, H. B. L. (2023). BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING. *Journal of Science & Technology*, *8*(7), 95–100. https://doi.org/10.46243/jst.2023.v8.i06.pp95-100

@article{hbhagyalakshmi2023brain,
  author    = {H BHAGYA LAKSHMI, H BHAGYA LAKSHMI},
  title     = {{BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING}},
  journal   = {Journal of Science \& Technology},
  year      = {2023},
  month     = {aug},
  volume    = {8},
  number    = {7},
  pages     = {95--100},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2023.v8.i06.pp95-100},
  url       = {https://doi.org/10.46243/jst.2023.v8.i06.pp95-100},
  language  = {en},
  abstract  = {Brain tumor is the main threat among the people. But currently, it become more advanced because of the many Machine Learning techniques. Magnetic Resonance Imaging is the greatest technique among all the image processing techniques which scans the human body and gives a clear resolution of the tumors in an improved quality image. The fundamentals of MRI are to develop images based on magnetic field and radio waves of the anatomy of the body. The major area of segmentation of images is medical image processing. Better results are provided by MRI images than CT scan, Xrays etc. Nowadays the automatic tumor detection in large spatial and structural variability. Recently Convolutional Neural Network plays an important role in medical field and computer vision. One of its application is the identification of brain tumor. Here, the pre-processing technique is used to convert normal images to grayscale values because it contains equal intensity but in MRI, RGB content is included. Then filtering is used to remove the unwanted noises using median and high pass filter for better quality of images. The deeper architecture design in CNN is performed using small kernels. Finally, the effect of using this network for segmentation of tumor from MRI images is evaluated with better results.}
}

TY  - JOUR
TI  - BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING
AU  - H BHAGYA LAKSHMI, H BHAGYA LAKSHMI
JO  - Journal of Science & Technology
PY  - 2023
DA  - 2023/08/07/
VL  - 8
IS  - 7
SP  - 95
EP  - 100
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - Brain tumor is the main threat among the people. But currently, it become more advanced because of the many Machine Learning techniques. Magnetic Resonance Imaging is the greatest technique among all the image processing techniques which scans the human body and gives a clear resolution of the tumors in an improved quality image. The fundamentals of MRI are to develop images based on magnetic field and radio waves of the anatomy of the body. The major area of segmentation of images is medical image processing. Better results are provided by MRI images than CT scan, Xrays etc. Nowadays the automatic tumor detection in large spatial and structural variability. Recently Convolutional Neural Network plays an important role in medical field and computer vision. One of its application is the identification of brain tumor. Here, the pre-processing technique is used to convert normal images to grayscale values because it contains equal intensity but in MRI, RGB content is included. Then filtering is used to remove the unwanted noises using median and high pass filter for better quality of images. The deeper architecture design in CNN is performed using small kernels. Finally, the effect of using this network for segmentation of tumor from MRI images is evaluated with better results.
DO  - 10.46243/jst.2023.v8.i06.pp95-100
UR  - https://doi.org/10.46243/jst.2023.v8.i06.pp95-100
ER  -

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    "URL": "https://doi.org/10.46243/jst.2023.v8.i06.pp95-100",
    "title": "BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING",
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    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "Brain tumor is the main threat among the people. But currently, it become more advanced because of the many Machine Learning techniques. Magnetic Resonance Imaging is the greatest technique among all the image processing techniques which scans the human body and gives a clear resolution of the tumors in an improved quality image. The fundamentals of MRI are to develop images based on magnetic field and radio waves of the anatomy of the body. The major area of segmentation of images is medical image processing. Better results are provided by MRI images than CT scan, Xrays etc. Nowadays the automatic tumor detection in large spatial and structural variability. Recently Convolutional Neural Network plays an important role in medical field and computer vision. One of its application is the identification of brain tumor. Here, the pre-processing technique is used to convert normal images to grayscale values because it contains equal intensity but in MRI, RGB content is included. Then filtering is used to remove the unwanted noises using median and high pass filter for better quality of images. The deeper architecture design in CNN is performed using small kernels. Finally, the effect of using this network for segmentation of tumor from MRI images is evaluated with better results.",
    "ISSN": "2456-5660"
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From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2023.v8.i06.pp95-100 gives all four in one JSON answer.