ISSN 2394-5125
 

Research Article 


DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran.

Abstract
Brain tumor means the aggregation of abnormal cells in some tissues of the brain. Brain tumor can be cancerous or noncancerous. The most common types of brain tumors are Glioma, Meningioma and Pituitary tumor. Early detection of tumor cells plays a major role in treatment and recovery of patient. Diagnosing a brain tumor usually undergoes a very complicated and time consuming process. The MRI images of various patients at various stages can be used for the detection of tumors. There are various types of feature extraction and classification methods which are used for detection of brain tumor from MRI images. Convolutional Neural Network image classification algorithm helps in detecting the tumor at early stage with high accuracy. We proposed a Recurrent Neural Network architecture for detection of tumor cells which gives accuracy of about 90%. A recurrent neural network (RNN) is a type of artificial neural networks in that connections between nodes form a directed graph along a temporal sequence.

Key words: Brain tumor, Convolutional Neural Networks, Recurrent Neural Network,Deep Learning


 
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How to Cite this Article
Pubmed Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran. DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING. JCR. 2020; 7(9): 347-350. doi:10.31838/jcr.07.09.74


Web Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran. DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING. http://www.jcreview.com/?mno=111627 [Access: April 18, 2021]. doi:10.31838/jcr.07.09.74


AMA (American Medical Association) Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran. DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING. JCR. 2020; 7(9): 347-350. doi:10.31838/jcr.07.09.74



Vancouver/ICMJE Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran. DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING. JCR. (2020), [cited April 18, 2021]; 7(9): 347-350. doi:10.31838/jcr.07.09.74



Harvard Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran (2020) DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING. JCR, 7 (9), 347-350. doi:10.31838/jcr.07.09.74



Turabian Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran. 2020. DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING. Journal of Critical Reviews, 7 (9), 347-350. doi:10.31838/jcr.07.09.74



Chicago Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran. "DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING." Journal of Critical Reviews 7 (2020), 347-350. doi:10.31838/jcr.07.09.74



MLA (The Modern Language Association) Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran. "DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING." Journal of Critical Reviews 7.9 (2020), 347-350. Print. doi:10.31838/jcr.07.09.74



APA (American Psychological Association) Style

R.C.Suganthe, G.Revathi, S.Monisha, R.Pavithran (2020) DEEP LEARNING BASED BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING. Journal of Critical Reviews, 7 (9), 347-350. doi:10.31838/jcr.07.09.74