Abstract
The objective of this paper is to segment the tumor part from the MRI brain images by utilizing optimization techniques. The RGB images are converted to grayscale images; then, the intensity is enhanced in grayscale images. After that, the skull stripping system is utilized for evacuating the skull, tissue, and so on from the contrast-enhanced images. The segmentation procedure is applied using the modified region growing segmentation, and this technique is performed with various optimization algorithms utilized for threshold optimization specifically spider social optimization (SSO) and web optimization (WO). These methods are compared with different parameters like sensitivity, specificity, and accuracy. The proposed system is executed in the working platform of MATLAB and results are compared using input images and output images.
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Srinivasa Reddy, A., Chenna Reddy, P. (2020). Enhanced Image Segmentation Using Application of Web Optimization for Brain Tumor Images. In: Satapathy, S., Bhateja, V., Mohanty, J., Udgata, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 159. Springer, Singapore. https://doi.org/10.1007/978-981-13-9282-5_27
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DOI: https://doi.org/10.1007/978-981-13-9282-5_27
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