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Article Name - Performance Evaluation of State-of-the-Art Texture Feature Extraction Techniques on Medical Imagery Tasks

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  • Keywords Content based image retrieval; Medical image retrieval; Texture feature extraction; Evaluation metrics; Similarity measurement ... 2023-07-06
  • Introduction Technology has advanced in numerous ways and most computer scientists are eager to bridge the gap between the capabilities of mankind and machines [1]. This is to say that, these scientists w ... 2023-07-06
  • Materials and Methods Experimental setup System requirements for the various models implemented require a minimum system specification to be met for a successful study. The specifications are categorized into har ... 2023-07-06
  • Results and Discussion In order to have a conclusive resulting data for the varying dataset ranging from 1 k-10.5 k, we sort to find the average of each metric for the various selected techniques/models [18-20]. Be ... 2023-07-06
  • Conclusion It can be concluded from this study that the local binary pattern is best suited for research that focuses on precision, F1-score, and apparently accuracy for content-based medical image retriev ... 2023-07-06
  • Summary The study compares the performance of the six selected texture feature extraction techniques on the medical dataset. Specifically, the performance metrics we are comparing are on the basis of p ... 2023-07-06
  • Disclosures The authors declare no conflicts of interest, financial or otherwise for this research. ... 2023-07-06
  • Acknowledgment First of all, I will like to use this opportunity to thank the almighty god, the creator of the universe for giving me the strength and ability to accomplish this task. I will like to also ex ... 2023-07-06
  • References Zin NA, Yusof R, Lashari SA, Mustapha A, Senan N, Ibrahim R. Content-based image retrieval in medical domain: A review. J Phys Conf Ser. 2018;1019(1):012044. [Crossref] [Google Scholar] ... 2023-07-06