Visual intelligence for robotic and laparoscopic surgery: A real-time System for bleeding detection
This event is in the past.
Detroit, MI 48202
Dr. Mostafa D. Rahbar, Assistant Professor, Lawrence Technological University
In the operation room, surgeons must always be precise when making incisions or performing other surgical tasks. The repetitive tasks are challenging. To assist surgeons, the medical field is using the advancements of AI and collaborative robots in the OR. Surgical robots can control the trajectory, depth, and speed of their movements with great precision. They are especially well-suited for procedures that require the same, repetitive movements as they can work without fatigue. Robots can also remain completely still for as long as needed and can go where traditional tools cannot.
Artificial intelligence is being applied to surgical robotics. AI can determine patterns within surgical procedures to improve best practices and to improve a surgical robots’ control accuracy to submillimeter precision. AI is also being used with machine vision to analyze scans and detect cancerous cases. Laparoscopic video analysis of surgeries, like sleeve gastrectomy procedures, helps to identify missing or unexpected steps in real time. This dissertation focuses on the application of artificial intelligence in the sense of hemorrhage during robotic surgery and proposes a practical method for predicting and handling these circumstances.
My research is focusing on designing the intelligent embedded integrated system to improve the surgeon’s performance in case of unexpected bleeding situations during robotic surgery. This improvement will be done through the following components:
- Design a mechanism for monitoring the surgery scene and predict the occurrence of bleeding
- Design preventive system to warn the surgeon about the abrupt movement of surgical tools
- Detect the pools of blood during the robotic surgery and contour them out
- Detect the moment of arterial bleeding during the surgery
- Overcome the complexity of visualization employing Augmented reality incorporated with a 3D model of robotic scene.
Dr. Mostafa D. Rahbar has been an assistant professor in the electrical and computer engineering department at Lawrence Technological University since January 2022. He attended the School of Engineering at Wayne State University and graduated with his Bachelor of Science in Electrical and Computer Engineering with a 4.0 GPA in May 2017. He received his Master of Science in Electrical Engineering in December 2018. He continued his graduate education and received a Doctoral of Philosophy degree in Electrical Engineering in December 2020 with a 4.0 GPA. Dr. Rahbar is a Ph.D.-level Electrical Engineer with seven years of teaching at Wayne State University, Cleveland State University, and Lawrence Technological University. His primary research expertise is in hardware and software development to support visual intelligence and automation for robotic surgery. Dr. Rahbar graduated at the top of his class in undergraduate and graduate school. He has two patents and several proposals and publications in this field.