AI-based texture classification
Interventional therapy provides minimally invasive, targeted treatment of Tumor. This procedure attracted a lot of attention because of minimizing possible injury to other body organs. During the minimal interventional therapy procedure, digital image data provide physicians a view of the inside body and assist them in decision making, planning, and evaluation of the therapy. However, low contrast in medical image data is a challenging task. Medical image in the field of the healthcare system plays a vital role and a lot of researchers in this area is come up with the idea to make physicians more efficient in their daily tasks. A0 Determination CT project aims to serve additional medical image information and assist clinicians in their decision. The direct impact of this project is on determining the stop points of therapy by acquiring sufficient knowledge about the characteristics of the various tissues appearing in interventional CT images during the therapy. The method explored in this project will allow differentiation between living and destroyed tumor cells based on the noise power behavior of the anatomical noise and AI-based classifiers. This very promising method will reduce tumor recurrence that leads to dose reduction in patients.
