Stereoscopic Near-Infrared Fluorescence Imaging: A Proof of Concept Toward Real-Time Depth Perception in Surgical Robotics
| Autor: | Stuart A. Bowyer, Ferdinando Rodriguez y Baena, Maxwell J. Munford |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Near-Infrared Fluorescence Imaging
active constraints Computer science lcsh:Mechanical engineering and machinery Stereoscopy lcsh:QA75.5-76.95 Imaging phantom law.invention Data acquisition Artificial Intelligence law Medical imaging stereoscopic near-infrared fluorescence lcsh:TJ1-1570 Computer vision Surgical robotics Original Research depth perception Robotics and AI real-time image acquisition business.industry Computer Science Applications NIRF imaging Proof of concept lcsh:Electronic computers. Computer science Artificial intelligence business Depth perception |
| Zdroj: | Frontiers in Robotics and AI Frontiers in Robotics and AI, Vol 6 (2019) |
| ISSN: | 2296-9144 |
| DOI: | 10.3389/frobt.2019.00066 |
| Popis: | The increasing use of surgical robotics has provoked the necessity for new medical imaging methods. Many assistive surgical robotic systems influence the surgeon's movements based on a model of constraints and boundaries driven by anatomy. This study aims to demonstrate that Near-Infrared Fluorescence (NIRF) imaging could be applied in surgical applications to provide subsurface mapping of capillaries beneath soft tissue as a method for imaging active constraints. The manufacture of a system for imaging in the near-infrared wavelength range is presented, followed by a description of computational methods for stereo-post-processing and data acquisition and testing used to demonstrate that the proposed methods are viable. The results demonstrate that it is possible to use NIRF for the imaging of a capillary submersed up to 11 mm below a soft tissue phantom, over a range of angles from 0° through 45°. Phantom depth has been measured to an accuracy of ±3 mm and phantom angle to a constant accuracy of ±1.6°. These findings suggest that NIRF could be used for the next generation of medical imaging in surgical robotics and provide a basis for future research into real-time depth perception in the mapping of active constraints. |
| Databáze: | OpenAIRE |
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