There is no doubt that CA enhances interventional procedures by providing useful information before, during, and after intervention, enabling the surgeon to observe important structures that might be missed. One future plan is to connect intraoperative assistance systems based on CA with robotic surgery systems. Robotic surgery enables surgeons to operate in fields where human-operated endoscopic surgery cannot reach. Micro-robotic surgery will allow us to perform sub-sub millimeter procedures. This means much more detailed information about human anatomy is strongly required for future surgery.
Feasibility of Intelligent Image Analysis with CA in High-Precision Radiation Treatment Planning
The aim of radiation therapy is to deliver as high a dose as possible to a target (i.e., a malignant lesion) to kill as many malignant cells as possible while minimizing the dose to healthy tissues or organs at risk (OAR). This requires exact localization of the target and OARs. Delineation of the contours of the gross tumor volume (GTV), which is defined as the visible tumor region identified in medical images, is key, because patient positioning and the optimization of radiation treatment planning (RTP) are performed based on the planning target volume (PTV) obtained from GTV . The OAR contours are also deeply involved in the optimization of the RTP. To address these requirements, many computational methods based on intelligent image analysis and/or CA have been studied with the aim of refining segmentation of targets and assisting determination of beam directions.
In this section, the feasibility of using intelligent image analysis and/or CA as an aid in high-precision RTP, including particle therapy, is explored.