CT Image Segmentation Using Optimization Techniques under Neutrosophic Domain
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Abstract
In this paper, we introduce a hybrid technique between optimization algorithms and neutrosophic theory. This new hybridization can deal with uncertainties in brain computed tomography (CT) images in three different memberships very effectively. To prove the real-time application of this theory, a new segmentation method for brain CT medical images is presented. The grayscale medical image suffers from uncertainties and inconsistencies in the gray levels due to their bad luminance. The proposed technique addressed this problem by performing neutrosophic operations on gray levels based on the S membership function.
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How to Cite
El-Shahat, D., Talal, N., Ye, J., & Cui, W.-H. (2024). CT Image Segmentation Using Optimization Techniques under Neutrosophic Domain. Neutrosophic Systems With Applications, 16, 1-11. https://doi.org/10.61356/j.nswa.2024.16203
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Research Articles
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
El-Shahat, D., Talal, N., Ye, J., & Cui, W.-H. (2024). CT Image Segmentation Using Optimization Techniques under Neutrosophic Domain. Neutrosophic Systems With Applications, 16, 1-11. https://doi.org/10.61356/j.nswa.2024.16203