Manuscript Number : IJSRST229249

Brain Tumor DetectionwithVGG-16 Model

Authors(5) :-R. Vadivel, Arnab Kumar Das, Uthej Kumar G, SK Abdul Sajid, Aaliya Ahmed K

A brain tumor is a life-threatening neurological condition caused by the unregulated development of cells inside the brain. Brain tumor can be very unforgiving to all age groups. The patient’s survival rate is usually very less, if they are not treated properly. Braintumorsaccountfor85%to90%ofallprimarycentral nervous system (CNS) tumors. Most ofthe times, survival rates decrease significantly with the age. While the anatomy of brain is more complex than any other vital organ, It becomes very crucial to find outthechancesofpeopledevelopingbraintumorinlaterstagesoflife.The segmentation, diagnosis, and isolation of contaminated tumor areas of brain from magnetic resonance (MRI) images is a prime concern. However, it is a very tedious and more time-consuming process that radiologists or clinical specialists must undertake and it soley depends on their performance and their expertise. In this paper, the different traditional and hybrid ML models were built and analyzed in detail, to classify the brain tumor images without any human intervention.Thefigureoffindingbraintumorinanindividuallifetimeis1inevery100[4].

Authors and Affiliations

R. Vadivel
Assistant Professor, Department of CSE, HKBKCE, Bangalore, Karnataka, India
Arnab Kumar Das
Assistant Professor, Department of CSE, HKBKCE, Bangalore, Karnataka, India
Uthej Kumar G
Assistant Professor, Department of CSE, HKBKCE, Bangalore, Karnataka, India
SK Abdul Sajid
Assistant Professor, Department of CSE, HKBKCE, Bangalore, Karnataka, India
Aaliya Ahmed K
Department of CSE, HKBKCE, Bangalore, Karnataka, India

Brain Tumor Classification, VGG-16CNN Model

  1. Brain tumor classification using deep CNN features via transfer learning Author links open overlay panelS.Deepak
  2. BrainMRNet: Brain tumor detection using magnetic resonance images with a novel convolutional neural network model Author links open overlay panelMesutTog˘ac¸ar
  3. CNN-LSTM: Cascaded Framework For Brain Tumour Classification Publisher: IEEE
  4. Statistical Insight about Brain Tumor. https://www.cancer.net/cancer- types/brain-tumor/statistics
  5. https://braintumor.org/brain-tumor-information/brain-tumor-facts
  6. https://www.cancer.net/cancer-types/brain-tumor/introduction
  7. https://blog.keras.io/how-convolutional-neural-networks-see-the- world.html
  8. https://pypi.org/project/opencv-python/
  9. https://blog.keras.io/building-powerful-image-classification-models-using- very-little-data.html
  10. https://towardsdatascience.com/keras-transfer-learning-for-beginners- 6c9b8b7143e
  11. https://www.pyimagesearch.com/2016/04/11/finding-extreme-points-in- contours-with-opencv
  12. https://www.pyimagesearch.com/2016/04/11/finding-extreme-points-in- contours-with-opencv

Publication Details

Published in : Volume 9 | Issue 2 | March-April 2022
Date of Publication : 2022-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 279-283
Manuscript Number : IJSRST229249
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

R. Vadivel, Arnab Kumar Das, Uthej Kumar G, SK Abdul Sajid, Aaliya Ahmed K, " Brain Tumor DetectionwithVGG-16 Model", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 9, Issue 2, pp.279-283, March-April-2022. Available at doi : https://doi.org/10.32628/IJSRST229249    
Journal URL : https://ijsrst.com/IJSRST229249
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