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  Authors

Dr. K.N.S. LAKSHMI,Ms. ANAPARTHI ALEKHYA SAI

  Keywords

Brain Tumors, Magnetic Resonance Imaging, VGG-16, Convolutional Neural Network (CNN) Model, Deep Learning Model, Abnormal Cell

  Abstract


Brain tumors have recently emerged as one of the most critical issues for individuals suffering from severe headaches. However, most people are concerned that their headache is the result of a serious problem, such as a brain tumor, especially if they experience severe pain on a regular basis. In general, practically all brain tumors do not induce headaches since the brain has the ability to modulate discomfort. Some tumor cause more frequent headaches if the patient's brain contains a large tumor that puts pressure on nerves. A brain tumor is a sort of abnormal cell that develops in the human brain and is always classified as benign or malignant. If the tumor is detected in its early stages and therapy is initiated, the quality of life and life spam may improve. There is currently a high need for brain tumor diagnosis using various machine learning and deep learning techniques. With the advancement of artificial intelligence, deep learning models are being used to diagnose brain tumors using magnetic resonance imaging pictures. Magnetic resonance imaging (MRI) is a sort of scanning procedure that produces detailed images of the inner body by using powerful magnetic fields and radio waves. Deep learning methods such as convolutional neural network (CNN) models and VGG-16 architecture (developed from scratch) are used in this study to locate tumor regions in scanned brain pictures. We looked at brain MRI scans from 253 patients, 155 of which were tumors and 98 of whom were not. The research compares the outputs of the CNN model and the VGG-16 architecture used.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2305280

  Paper ID - 236190

  Author type - Indian Author

  Page Number(s) - c177-c186

  Pubished in - Volume 11 | Issue 5 | May 2023

  DOI (Digital Object Identifier) -   

  No Of Downloads - 104

  Author Country - India, -, -, -, -, Science and Technology

  Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2305280

  Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT2305280

  Published Paper PDF Downlaod: - download.php?file=IJCRT2305280

  Cite this article

Dr. K.N.S. LAKSHMI,Ms. ANAPARTHI ALEKHYA SAI,   "DEEP LEARNING MODELS FOR BRAIN TUMOR DETECTION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 5, pp.c177-c186, May 2023, Available at :http://www.ijcrt.org/papers/IJCRT2305280.pdf

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