Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/1736 2018 2018 Department of AI&DS, Panimalar Engineering College, Chennai, 600123, India C. S. Manigandaa Department of Computer Engineering, Mizoram University, Aizawl 796004. India V. D. Ambeth Kumar Department of Computer Engineering, Mizoram University, Aizawl 796004. India G. Ragunath Computer Science and Engineering, Karunya University, Coimbatore 641114, India R. Venkatesan Department of Biotechnology, Mizoram University, Aizawl, Mizoram, 796004, India N. Senthil Kumar 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. 2023 2023 111 123 10.54216/FPA.110208 https://www.americaspg.com/articleinfo/3/show/1736