Publication Date: 2023/06/15
Abstract: One of the most important and most difficult tasks in medical imaging is the segmentation of brain tumors because human classification of books can lead to errors and diagnostic errors. Specifically, this study uses MRI images to identify brain tumors. A brain biopsy is not usually done before brain surgery and is used to isolate brain tumors. Technology and machine learning could help radiologists make tumors without using invasive procedures. There are two types of brain tumors: benign and malignant. The quality of life and life expectancy of these patients improves with early and timely disease detection and treatment planning. Convolutional neural network (CNN) is a machine learning technique that is incredibly successful in image segmentation and classification. We describe a new CNN architecture to classify three types of brain diseases. The created network is smaller than the existing pre-trained network.
Keywords: Brain tumor, Magnetic resonance imaging, Adaptive Bilateral Filter, Convolution Neural Network. Introduction.
DOI: https://doi.org/10.5281/zenodo.8041520
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23MAY1960.pdf
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