Enhanced DBN-based Thyroid Segmentation and Classification of US Images using Coyote Optimization Algorithm

Shankarlal, B. and Sathya, P. D. and Sureshkumar, G. and Dhivya, S. and Sudarsan, H. (2022) Enhanced DBN-based Thyroid Segmentation and Classification of US Images using Coyote Optimization Algorithm. In: UNSPECIFIED.

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Abstract

In this paper, a novel deep learning method is introduced for accurately segmenting and classiMng the thyroidL Here, the dataset is gathered from the standard sources. Next, the median filtering performs the preprocessing process. Further, the watershed segmentation is performedL Additionally, GLCM is used for extracting the features. In the final step, the classification is accomplished by the enhanced DBN, where the hidden neurons of DBN are optimized by COA thus known to be enhanced DBN. This enhanced DBN classifies the final output into normal and abnormal images. Simulation findings demonstrate the superiority of the proposed model. © 2022 Elsevier B.V., All rights reserved.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science > Artificial Intelligence
Divisions: Engineering and Technology > Vinayaka Mission's Kirupananda Variyar Engineering College, Salem > Electrical & Electronics Engineering
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 02 Dec 2025 09:27
URI: https://vmuir.mosys.org/id/eprint/2904

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