January 2019
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5 Reads
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2 Citations
International Journal of Biomedical Engineering and Technology
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Publications (3)
January 2019
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3 Reads
·
2 Citations
International Journal of Biomedical Engineering and Technology
June 2017
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73 Reads
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1 Citation
Journal of Medical Imaging and Health Informatics
In numerous uses of image processing and computer vision, it is image segmentation that is generally utilized. A given image is divided to distinctive areas by utilizing the division procedure taking into account some decisive factors. The investigation of the Computed Tomography (CT) images considers image division a critical and imperative part in recognizing the various types of tumor. The tumor's grouping and the non-tumor images took after by the segmentation of tumor locale in CT images is finished by the proposed methodology. The process of classifying is carried out by Adaptive Neuro-Fuzzy Inference System (ANFIS) classifier. It combines the explicit knowledge representation of an FIS and the learning power of the artificial neural networks. After the classification segmented the tumor part of the image, here fuzzy, c means clustering (FCM) technique with centroid optimization. As regards the centroid optimization Gray Wolf Optimizer (GWO) are used to increase the accuracy of the proposed approach. An accuracy rate of 99.24% in the analysis of the segmentation process is obtained Using GWO technique and Proposed FCM approach compared to existing technique the accuracy is 57.7%. It is in the working platform of MATLAB that this proposed methodology is implemented.
Citations (3)
... Various studies has classified the text (Singh and Singla, 2017;Ali Reshi and Singh, 2018;Audebert et al., 2020) for classification of text into two or more classes. The current study of image-based document classification applies image-based classification techniques (Anter et al., 2013;Aziz et al., 2013;Jothi et al., 2013;Emary et al., 2014aEmary et al., , 2014bThiruvenkatasuresh and Venkatachalam, 2019;Ferrando et al., 2020;Siddiqui et al., 2021). researchers have employed text-based, image-based and fusion (using both image and text) techniques for the image-based document classification. ...
- Citing Article
January 2019
International Journal of Biomedical Engineering and Technology
... Various studies has classified the text (Singh and Singla, 2017;Ali Reshi and Singh, 2018;Audebert et al., 2020) for classification of text into two or more classes. The current study of image-based document classification applies image-based classification techniques (Anter et al., 2013;Aziz et al., 2013;Jothi et al., 2013;Emary et al., 2014aEmary et al., , 2014bThiruvenkatasuresh and Venkatachalam, 2019;Ferrando et al., 2020;Siddiqui et al., 2021). researchers have employed text-based, image-based and fusion (using both image and text) techniques for the image-based document classification. ...
- Citing Article
January 2019
International Journal of Biomedical Engineering and Technology
... The fuzzy logical Inference System employed for husbanding and guiding these employs stress of human and to execute it, and notify by the alarm. Thiruvenkatasuresh, M. P. and Venkatachalam, V. introduced a Fuzzy Inference System to identification the assorted diseases supported initial symptoms. Diagnose the liver disease in their analysis (Thiruvenkatasuresh,, et. al., 2017) . They introduce -New Hybrid liver disease identification System supported Genetic formula and adaptive Network Fuzzy Inference System‖, planned Associate in nursing skilled system victimization Fuzzy Inference System to diagnose and monitor infectious disease (Sculpher, et. al., 2000) . ...
- Citing Article
June 2017
Journal of Medical Imaging and Health Informatics