Computer Vision News - July 2022

41 AI-Assisted Tissue Sparing in Urology and nerves. Such precision can be enhanced by fusing pre-op images from CT or MRI with the tumor segmentation, with the intra-op video, ultrasound or X-ray images. The surgeon can view in real-time the surgical plan and perform accordingly. The pre-op segmentation can be easily obtained using neural-networks trained to segment tumors. The registration process can be achieved using deep learning techniques and classic computer vision, and further improved using existing or wearable landmarks designated for image registration. (3) The above-described solutions assist in visualizing the tumor throughout the procedure. However, accuracy still depends on the tool-handling capabilities of the surgeon. To neutralize this effect, robots can be introduced. Robotic assisted surgeries (RAS) are becoming increasingly common. As expected, the robot’s “hand” is more stable than the human hand, and can perform these surgeries with increased accuracy and precision. To improve robotic accuracy, distinct key points within the anatomy can be selected, and the tools’ position relative to them can be calculated. This information provides real-time notifications of proximity to the tissue and warns against undesired resections. By using tool tracking algorithms - a well-established method which segments the tool in the field-of-view and utilizes prior knowledge of camera and tool characteristics to accurately position the tool in space - tool tracking is achieved. The robot can use this information to accuratelymaneuver thetoolwhileavoiding unnecessary incisions. This can also be done using electro-magnetic (EM) tracking - a designated EM sensor is attached to the tool and using an external EM field the tool’s position is recorded continuously. Further developments in this field may also register the robot's coordinate system with the patient’s, providing more accurate positioning relative to the anatomy. Now the surgeon can approach the surgical procedurewith high accuracy and stability , ensuring minimal surrounding damage, and sparing healthy tissue. Combining these methodologies can aid in tissue sparing during urologic procedures. A smaller port in an ideal position can be achieved without compromising the anatomical understanding of the surgical scene, the surgical target can be accurately viewed in real-time, and introduction of RAS will increase surgical accuracy, ultimately leading to less damage to healthy tissue. These solutions are challenging to implement, and advanced knowledge in AI and computer vision is essential for developing them. RSIP Vision has vast experience in developing computer vision solutions. Contact us for a speedy development process and faster time-to- market.