Development of Robotic Systems for Precision Tumor Resection

Abstract

As a big step forward in surgery, the creation of robotic systems for precise tumor removal promises higher accuracy, lower rates of complications, and better results for patients. Traditional surgery methods often have problems, like not being able to see well, be precise, or get to tumors that are hard to get to. Robotic systems that are combined with advanced imaging technologies give doctors high accuracy and real-time feedback. This lets them do minimally invasive treatments that lower the risk of damaging tissue. These systems have many important advantages, such as better agility, better 3D vision, and the ability to do complicated moves that humans can't do on their own. This study looks into how to plan, build, and use robotic systems for removing tumors in the body. The main goal is to create a framework that blends advanced imaging methods like MRI and CT scans with robotic handling so that tumors can be found and targeted with the utmost accuracy. Machine learning techniques are also built in to help find the location of tumors, make changes in real time during the process, and use forecast analytics to create surgery plans that are special to each patient. The results of this study show that robotic systems can make tumor resections much more accurate, shorten healing times, and lower the risk of surgery mistakes. Adding AI-powered decision-making tools makes it even easier to adapt processes to the specific needs of each patient, which improves the result of treatment. In the future, these technologies will keep getting better by being combined with new technologies like virtual reality and physical feedback. This will make robotic-assisted tumor resections even safer and more effective.