Framework using Diagnosis and CBIR System for Identifying Contrast Agent Concentration

Detection of cancerous cells is one of the conventional problems in medical image processing. Although there were many attempts to perform an investigation and come out with an efficient framework that ensures somewhat reliable detection. However, very few studies have focused on detecting the contrast agent exclusively in prostate cancer. Identifying the contrast agent precisely can assist the physician to perform correct diagnosis of the patient suffering from prostate cancer and thereby it becomes possible for the physician to recommend correct treatment. In this paper, we propose a framework that takes the input of a radiological image and perform adaptive independent component analysis, reference region (RR- based method) and Pharmacokinetic modeling (PK-Modeling) for highlighting the effective intravascular contrast concentration agent. The system is rendered more precise by incorporating CBIR system using visual descriptor