Journal
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
Volume 12, Issue 7, Pages 6911-6922Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s12652-020-02336-w
Keywords
Computer aided; Convolution neural network; Magnetic resonance imaging; Medical images; Tumor
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Brain tumor is a life-threatening disease caused by cell proliferation in the brain, and timely diagnosis and treatment are essential. This paper proposed a computer-aided approach using 2D convolutional neural network to classify brain MRI images with higher accuracy compared to other methods.
Brain tumor can be considered to be a fatal and life-threatening disease caused by undesirable cell proliferation in the human brain. Out of the several diseases in the field of medical science, brain tumor turns out to be one of the most uncompromising problems. A tumor can be categorized as benign or malignant types in which benign tumors are non-cancerous while malignant tumors are cancerous tumors. There are numerous tumor detection methods but there are still more research going on in this area since quantitative analysis, an accurate disease diagnosis and detection of brain tumor are very much essential with scientific proofs. Therefore, timely planning can be prepared to save a person's life with brain tumor. This paper presents a computer aided approach with a 2D convolutional neural network for classifying the brain MRI images into two classes: Normal class and tumor class. In this paper, other classification methods are also used for comparison. The results are compared in terms of precision value, Recall value, F1-Score value. This proposed method shows better accuracy of 97% than the other methods.
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