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Fusion: Practice and Applications

Volume 11 , Issue 2 , PP: 111-123, 2023 | Cite this article as | XML | Html | PDF | Full Length Article

De-Noising and Segmentation of Medical Images using Neutrophilic Sets

C. S. Manigandaa 1 * , V. D. Ambeth Kumar 2 , G. Ragunath 3 , R. Venkatesan 4 , N. Senthil Kumar 5

  • 1 Department of AI&DS, Panimalar Engineering College, Chennai, 600123, India - (csmanigandaa@gmail.com)
  • 2 Department of Computer Engineering, Mizoram University, Aizawl 796004. India - (ambeth@mzu.edu.in)
  • 3 Department of Computer Engineering, Mizoram University, Aizawl 796004. India - (ragunath2004112@gmail.com)
  • 4 Computer Science and Engineering, Karunya University, Coimbatore 641114, India - (rlvenkei_2000@karunya.edu)
  • 5 Department of Biotechnology, Mizoram University, Aizawl, Mizoram, 796004, India - (nskmzu@gmail.com)

    • Doi: https://doi.org/10.54216/FPA.110208

    Received: December 20, 2022 Accepted: April 26, 2023
    Abstract

    Medical diagnosis and prognosis are challenging tasks due to subjectivity and inherent uncertainty in medical images. Inconsistencies in expert opinions can result in incorrect diagnoses. Neutrosophic theory, a mathematical framework that deals with imprecise or incomplete data, has shown promise in addressing the challenges posed by medical image processing. A neutrosophic theory approach is explored in this paper for de-noising and segmenting medical images. Neutrosophic theory has been utilized to represent the different degrees of truth in each piece of information, resulting in better performance in de-noising and segmentation tasks. Neutosophic theory presents a promising avenue for future investigation in medical image processing as shown in this study.

    Keywords :

    neutrophilic set , medical image , Noise , Segmentation

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    Cite This Article As :
    S., C.. , D., V.. , Ragunath, G.. , Venkatesan, R.. , Senthil, N.. De-Noising and Segmentation of Medical Images using Neutrophilic Sets. Fusion: Practice and Applications, vol. , no. , 2023, pp. 111-123. DOI: https://doi.org/10.54216/FPA.110208
    S., C. D., V. Ragunath, G. Venkatesan, R. Senthil, N. (2023). De-Noising and Segmentation of Medical Images using Neutrophilic Sets. Fusion: Practice and Applications, (), 111-123. DOI: https://doi.org/10.54216/FPA.110208
    S., C.. D., V.. Ragunath, G.. Venkatesan, R.. Senthil, N.. De-Noising and Segmentation of Medical Images using Neutrophilic Sets. Fusion: Practice and Applications , no. (2023): 111-123. DOI: https://doi.org/10.54216/FPA.110208
    S., C. , D., V. , Ragunath, G. , Venkatesan, R. , Senthil, N. (2023) . De-Noising and Segmentation of Medical Images using Neutrophilic Sets. Fusion: Practice and Applications , () , 111-123 . DOI: https://doi.org/10.54216/FPA.110208
    S. C. , D. V. , Ragunath G. , Venkatesan R. , Senthil N. [2023]. De-Noising and Segmentation of Medical Images using Neutrophilic Sets. Fusion: Practice and Applications. (): 111-123. DOI: https://doi.org/10.54216/FPA.110208
    S., C. D., V. Ragunath, G. Venkatesan, R. Senthil, N. "De-Noising and Segmentation of Medical Images using Neutrophilic Sets," Fusion: Practice and Applications, vol. , no. , pp. 111-123, 2023. DOI: https://doi.org/10.54216/FPA.110208

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