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Accurate Detection of Brain Tumor Using Optimized Feature Selection Based on Deep Learning Techniques by Praveen Kumar Ramtekkar; Anjana Pandey; Mahesh Kumar Pawar is a Computer Science article available to read on EtoBox.

What is Accurate Detection of Brain Tumor Using Optimized Feature Selection Based on Deep Learning Techniques about?

An unusual increase of nerves inside the brain, which disturbs the actual working of the brain, is called a brain tumor. It has led to the death of lots of lives. To save people from this disease timely detection and the right cure is the need of time. Finding of tumor-affected cells in the human brain is a cumbersome and time-consuming task. However, the accuracy and time required to detect brain tumors is a big challenge in the arena of image processing. This research paper proposes a novel, accurate and optimized system to detect brain tumors. The system follows the activities like, preprocessing, segmentation, feature extraction, optimization and detection. For preprocessing system uses a compound filter, which is a composition of Gaussian, mean and median filters. Threshold and histogram techniques are applied for image segmentation. Grey level co-occurrence matrix (GLCM) is used for feature extraction. The optimized convolution neural network (CNN) technique is applied here that uses whale optimization and grey wolf optimization for best feature selection. Detection of brain tumors is achieved through CNN classifier. This system compares its performance with another modern te

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Author

Praveen Kumar Ramtekkar; Anjana Pandey; Mahesh Kumar Pawar

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)