ISSN 2394-5125
 

Research Article 


PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING

Suraj Patil, Dr D. K. Kirange, Varsha Nemade.

Abstract
In recent years, prediction and analysis of human brain tumor have
become one of the most challenging issues in healthcare science. Various machine
learning algorithms are designed to automate the process of detection of brain tumor.
Because of the popularity of computer vision in AI, the segmentation of tumor in
unstructured data set such as brain MRI and its analysis as become an important part
of the diagnosis of cancer at an early stage. The correct diagnosis is a very crucial and
critical step and depends on the expertise of doctors and radiologists. The deep
learning models are getting a lot of popularity in the detection of tumors because its
accuracy. In this paper, we designed deep learning architectures for detection of
tumors in Magnetic Resonance Imaging (MRI) image. In the proposed architecture,
firstly, the convolution neural network (CNN) architecture was designed from scratch
using Keras library; secondly, the architecture of CNN was tuned by adjusting hyper
parameter and increasing number of layers, and finally the transfer learning
mechanism was implemented by using weights of VGG16 architecture. The
performance of all models was evaluated using confusion matrix on validation and the
test data set. The result shows that adjusting hyper parameter and transfer learning the
accuracy of detection of tumor can be improved. In addition, this deep learning model
detects human brain tumors within seconds as compared to other machine learn- ing
algorithm.

Key words: Magnetic Resonance Imaging(MRI), hyper parameter, CNN, VGG16, Ke- ras,transfer learning.


 
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Pubmed Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade. PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING. JCR. 2020; 7(4): 1805-1813. doi:10.31838/jcr.07.04.296


Web Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade. PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING. http://www.jcreview.com/?mno=118726 [Access: April 12, 2021]. doi:10.31838/jcr.07.04.296


AMA (American Medical Association) Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade. PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING. JCR. 2020; 7(4): 1805-1813. doi:10.31838/jcr.07.04.296



Vancouver/ICMJE Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade. PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING. JCR. (2020), [cited April 12, 2021]; 7(4): 1805-1813. doi:10.31838/jcr.07.04.296



Harvard Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade (2020) PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING. JCR, 7 (4), 1805-1813. doi:10.31838/jcr.07.04.296



Turabian Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade. 2020. PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING. Journal of Critical Reviews, 7 (4), 1805-1813. doi:10.31838/jcr.07.04.296



Chicago Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade. "PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING." Journal of Critical Reviews 7 (2020), 1805-1813. doi:10.31838/jcr.07.04.296



MLA (The Modern Language Association) Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade. "PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING." Journal of Critical Reviews 7.4 (2020), 1805-1813. Print. doi:10.31838/jcr.07.04.296



APA (American Psychological Association) Style

Suraj Patil , Dr D. K. Kirange, Varsha Nemade (2020) PREDICTIVE MODELLING OF BRAIN TUMOR DETECTION USING DEEP LEARNING. Journal of Critical Reviews, 7 (4), 1805-1813. doi:10.31838/jcr.07.04.296