Abstract
In this document, we employed an efficient Optimal GLCM attribute related FCM segmentation algorithm which is used to categorize the kidney cysts and tumor from the ultrasound kidney images. The FCM is exploiting some appropriate attributes of GLCM texture feature extractor and optimally attach the cluster centroids of FCM by the help of Whale optimization algorithm. The proposed approach is executed in the working platform of Matlab. The findings demonstrate that the proposed model have better performance in recognizing the detection of kidney cysts and tumor in patients by examining US kidney images. Also, we have shown the comparison of our proposed method FB-FCM-WOA with the existing methodologies like FB-FCM, FB-K-means, IB-FCM and IB-K-means. Hence, we would suggest that our proposed method is much better for detecting kidney cysts and tumor.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
