Encryption and enhance medical image using hybrid transform (Ã-module and partial fuzzy Ȟ-transform)

Abstract

This research provides a novel application for fuzzy partial differential equations in the biomedical and engineering sectors. To create this program, we multiplied the Ã-module by the fuzzy partial F-transform, which yielded a new transform that was then used as a filter in image processing. Around 6 percent of all cancer cases in adults are caused by people under 20, and most cancers begin as acute interstitial pneumonia. In recent years, many oncologists have used mathematical models to draw conclusions and make forecasts. This is by experimental biological models. Based on the newly proposed rational valued cyclic group characters and partial fuzzy transformation, this study proposes a novel method for image processing of diseased cells, which involves solving such concepts as encoding and differentiating parameters, optimizing radiographic images, and converting the idea into a filter. Radiographic image optimization and parameter differentiation were also part of the study. It was shown that the suggested transformation provided much higher levels of intelligibility than the fuzzy partial Laplace transform analysis and categorization of how a patient’s illness trajectory affects their responsiveness to treatment.