A Real-Time Interactive Augmented Reality Depth Estimation Technique for Surgical Robotics

Augmented reality (AR) is a promising technology where the surgeon can see the medical abnormality in the context of the patient. It makes the anatomy of interest visible to the surgeon which otherwise is not visible. It can result in better surgical precision and therefore, potentially better surgical outcomes and faster recovery times. Despite these benefits, the current AR systems suffer from two major challenges; first, incorrect depth perception and, second, the lack of suitable evaluation systems. Therefore, in the current paper we addressed both of these problems. We proposed a color depth encoding (CDE) technique to estimate the distance between the tumor and the tissue surface using a surgical instrument. We mapped the distance between the tumor and the tissue surface to the blue-red color spectrum. For evaluation and interaction with our AR technique, we propose to use a virtual surgical instrument method using the CAD model of the instrument. The users were asked to reach the judged distance in the surgical field using the virtual tool. Realistic tool movement was simulated by collecting the forward kinematics joint encoder data. The results showed significant improvement in depth estimation, time for task completion and confidence, using our CDE technique with and without stereo versus other two cases, that are, Stereo-No CDE and No Stereo-No CDE.

[1]  D. Louis Collins,et al.  The state of the art of visualization in mixed reality image guided surgery , 2013, Comput. Medical Imaging Graph..

[2]  Guang-Zhong Yang,et al.  pq-space Based Non-Photorealistic Rendering for Augmented Reality , 2007, MICCAI.

[3]  Alvy Ray Smith,et al.  Color gamut transform pairs , 1978, SIGGRAPH.

[4]  Werner Frei,et al.  Fast Boundary Detection: A Generalization and a New Algorithm , 1977, IEEE Transactions on Computers.

[5]  Michael Kalloniatis,et al.  The Perception of Depth , 2007 .

[6]  Ryutarou Ohbuchi,et al.  Merging virtual objects with the real world: seeing ultrasound imagery within the patient , 1992, SIGGRAPH.

[7]  D. Louis Collins,et al.  Augmented Reality in Neurovascular Surgery: First Experiences , 2014, AE-CAI.

[8]  Nassir Navab,et al.  Auditory and Visio-Temporal Distance Coding for 3-Dimensional Perception in Medical Augmented Reality , 2015, 2015 IEEE International Symposium on Mixed and Augmented Reality.

[9]  A. Meola,et al.  Augmented reality in neurosurgery: a systematic review , 2017, Neurosurgical Review.

[10]  D. Hill,et al.  Augmentation of reality using an operating microscope for otolaryngology and neurosurgical guidance. , 1995, Journal of image guided surgery.

[11]  Eric Kolstad,et al.  The Effects of Virtual Reality, Augmented Reality, and Motion Parallax on Egocentric Depth Perception , 2008, VR.

[12]  Tobias Ortmaier,et al.  Color-encoded distance for interactive focus positioning in laser microsurgery , 2016 .

[13]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  S. Umeyama,et al.  Least-Squares Estimation of Transformation Parameters Between Two Point Patterns , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Nassir Navab,et al.  Contextual Anatomic Mimesis Hybrid In-Situ Visualization Method for Improving Multi-Sensory Depth Perception in Medical Augmented Reality , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.

[16]  Lejing Wang,et al.  Augmented reality during angiography: Integration of a virtual mirror for improved 2D/3D visualization , 2012, 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR).

[17]  James E. Cutting,et al.  Chapter 3 – Perceiving Layout and Knowing Distances: The Integration, Relative Potency, and Contextual Use of Different Information about Depth* , 1995 .

[18]  D. Louis Collins,et al.  An Evaluation of Depth Enhancing Perceptual Cues for Vascular Volume Visualization in Neurosurgery , 2014, IEEE Transactions on Visualization and Computer Graphics.

[19]  Nassir Navab,et al.  On mixed reality environments for minimally invasive therapy guidance: Systems architecture, successes and challenges in their implementation from laboratory to clinic , 2013, Comput. Medical Imaging Graph..

[20]  Ronald Azuma,et al.  A Survey of Augmented Reality , 1997, Presence: Teleoperators & Virtual Environments.

[21]  Heinz-Otto Peitgen,et al.  Illustrative visualization of 3D planning models for augmented reality in liver surgery , 2010, International Journal of Computer Assisted Radiology and Surgery.

[22]  Lejing Wang,et al.  First Deployments of Augmented Reality in Operating Rooms , 2012, Computer.

[23]  Deborah Hix,et al.  A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality , 2006, IEEE Virtual Reality Conference (VR 2006).

[24]  Bernhard Preim,et al.  Combining Pseudo Chroma Depth Enhancement and Parameter Mapping for Vascular Surface Models , 2017, VCBM.

[25]  Nassir Navab,et al.  Depth Perception - A Major Issue in Medical AR: Evaluation Study by Twenty Surgeons , 2006, MICCAI.

[26]  D. Louis Collins,et al.  Augmented Reality Visualization for Guidance in Neurovascular Surgery , 2012, MMVR.

[27]  Christian Winne,et al.  Overlay visualization in endoscopic ENT surgery , 2011, International Journal of Computer Assisted Radiology and Surgery.

[28]  E.M. Friets,et al.  A frameless stereotaxic operating microscope for neurosurgery , 1989, IEEE Transactions on Biomedical Engineering.

[29]  Terry M. Peters,et al.  Training for Planning Tumour Resection: Augmented Reality and Human Factors , 2015, IEEE Transactions on Biomedical Engineering.

[30]  Philip Pratt,et al.  Transoral Robotic Surgery: Image Guidance and Augmented Reality , 2018, ORL.