A Method for Removing PET/CT Imaging Artifact Using Combination of Standard Deviation and Computational Geometry Technique

Abstract Positron emission tomography/Computed tomography is a non-intrusive imaging methodology, which is clinically utilized for both finding and getting to treatment reaction in oncology, cardiology, as well as neurology. Many different artifacts can occur during Positron emission tomography (PET) imaging, these artifacts are expected essentially to metallic inserts, respiratory movement, utilization of contrast media also image truncation. Artifacts are relatively common in PET/CT imaging and may potentially degrade image quality and interfere with accurate radiological reporting and diagnosis. Improving the recognition of PET/CT artifacts may assist imaging practitioners to avoid or limit their effect on image quality and interpretation. This paper proposed a statistical method of standard deviation to figure the global threshold for binarizing image and computational geometry to reach the output. This combination would produce good results for removing the artifacts from pancreatic PET/CT images