Visual servoing in medical robotics: a survey. Part II: tomographic imaging modalities--techniques and applications.

BACKGROUND: Intraoperative application of tomographic imaging techniques provides a means of visual servoing for objects beneath the surface of organs. METHODS: The focus of this survey is on therapeutic and diagnostic medical applications where tomographic imaging is used in visual servoing. To this end, a comprehensive search of the electronic databases was completed for the period 2000-2013. RESULTS: Existing techniques and products are categorized and studied, based on the imaging modality and their medical applications. This part complements Part I of the survey, which covers visual servoing techniques using endoscopic imaging and direct vision. CONCLUSION: The main challenges in using visual servoing based on tomographic images have been identified. 'Supervised automation of medical robotics' is found to be a major trend in this field and ultrasound is the most commonly used tomographic modality for visual servoing.

Visual servoing in medical robotics: a survey. Part I: endoscopic and direct vision imaging - techniques and applications.

BACKGROUND: Intra-operative imaging is widely used to provide visual feedback to a clinician when he/she performs a procedure. In visual servoing, surgical instruments and parts of tissue/body are tracked by processing the acquired images. This information is then used within a control loop to manoeuvre a robotic manipulator during a procedure. METHODS: A comprehensive search of electronic databases was completed for the period 2000-2013 to provide a survey of the visual servoing applications in medical robotics. The focus is on medical applications where image-based tracking is used for closed-loop control of a robotic system. RESULTS: Detailed classification and comparative study of various contributions in visual servoing using endoscopic or direct visual images are presented and summarized in tables and diagrams. CONCLUSION: The main challenges in using visual servoing for medical robotic applications are identified and potential future directions are suggested. 'Supervised automation of medical robotics' is found to be a major trend in this field.

Image-guided techniques in renal and hepatic interventions.

BACKGROUND: Development of new imaging technologies and advances in computing power have enabled the physicians to perform medical interventions on the basis of high-quality 3D and/or 4D visualization of the patient's organs. Preoperative imaging has been used for planning the surgery, whereas intraoperative imaging has been widely employed to provide visual feedback to a clinician when he or she is performing the procedure. In the past decade, such systems demonstrated great potential in image-guided minimally invasive procedures on different organs, such as brain, heart, liver and kidneys. This article focuses on image-guided interventions and surgery in renal and hepatic surgeries. METHODS: A comprehensive search of existing electronic databases was completed for the period of 2000-2011. Each contribution was assessed by the authors for relevance and inclusion. The contributions were categorized on the basis of the type of operation/intervention, imaging modality and specific techniques such as image fusion and augmented reality, and organ motion tracking. RESULTS: As a result, detailed classification and comparative study of various contributions in image-guided renal and hepatic interventions are provided. In addition, the potential future directions have been sketched. CONCLUSION: With a detailed review of the literature, potential future trends in development of image-guided abdominal interventions are identified, namely, growing use of image fusion and augmented reality, computer-assisted and/or robot-assisted interventions, development of more accurate registration and navigation techniques, and growing applications of intraoperative magnetic resonance imaging.

Applications of artificial intelligence in safe human-robot interactions.

The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.