This paper reports the development and system analysis of a laparoscopic system based on structured illumination technique capable of three-dimensional (3-D) reconstruction of porcine intestine during surgical anastomosis (connection of tubular structures). A calibration target is used to validate the system performance and results show a depth of field of 20 mm with an accuracy of 0.008 mm and precision of 0.25 mm. The imaging system is used to reconstruct a quantitative 3-D depth measurement of ex vivo porcine bowel tissues to mimic an end-to-end bowel anastomosis scenario. We demonstrate that the system can detect a suture in the tissue and map homogeneous surfaces of the intestine with different tissue pigments, affirming the feasibility for depth quantization for guiding and assisting medical diagnostic decisions in anastomosis surgery.
Surgical 3D endoscopy based on structured illumination has been built and evaluated for application in minimally invasive anastomosis surgery which offers advantages of smaller incision, low risk of infection, quick recovery times and reduced blood loss. When combined with robotic manipulations, surgeons can perform surgical tasks with higher precision and repeatability. For reconstructive surgery such as anastomosis, a supervised laparoscopic anastomosis using a surgical robot has recently been reported with an open-surgery approach using a large 3D camera. To push the technology into minimally-invasive setting, we report an endoscopic 3D system based on structured illumination technique to assist the surgical robot, particularly in anastomosis surgery. The recorded structural profile achieves a high depth quantification of 250 um for static objects, with 25 mm depth of field. The proposed system can be integrated into a flexible holding arm to move in accordance with the surgical robotic arm. We characterize the system performance using multiple porcine intestinal tissue samples with variations in surface textures, tissue pigmentation and thickness.
Proc. SPIE. 10220, Dimensional Optical Metrology and Inspection for Practical Applications VI
KEYWORDS: Eye, Three dimensional sensing, Cameras, Calibration, Image processing, Distortion, Motion detection, Digital imaging, Vibrometry, 3D metrology, Machine vision, Digital image correlation, 3D vision, 3D image processing
Image matching involves detecting the same points in two or multiple images that are captured from different viewpoints, at different time, and/or by different cameras. This paper presents using the image-matching-based techniques to carry out the static and dynamic 3D shape measurements. The process contains two crucial steps: (1) calibrate the cameras to get the intrinsic and extrinsic parameters; (2) perform matching of pixel points to detect the location disparities of the same physical points in the involved two or multiple images. A number of experiments are shown to demonstrate the applications to 3D shape, deformation, motion and vibration measurements.
Surgeons have been increasingly relying on minimally invasive surgical guidance techniques not only to reduce surgical trauma but also to achieve accurate and objective surgical risk evaluations. A typical minimally invasive surgical guidance system provides visual assistance in two-dimensional anatomy and pathology of internal organ within a limited field of view. In this work, we propose and implement a structure illumination endoscope to provide a simple, inexpensive 3D endoscopic imaging to conduct high resolution 3D imagery for use in surgical guidance system. The system is calibrated and validated for quantitative depth measurement in both calibrated target and human subject. The system exhibits a depth of field of 20 mm, depth resolution of 0.2mm and a relative accuracy of 0.1%. The demonstrated setup affirms the feasibility of using the structured illumination endoscope for depth quantization and assisting medical diagnostic assessments
It is demonstrated that audio information can be extracted from silent high-speed video with a simple and fast optical technique. The basic principle is that the sound waves can stimulate objects encountered in the traveling path to vibrate. The vibrations, although usually with small amplitudes, can be detected by using an image matching process. The proposed technique applies a subset-based image correlation approach to detect the motions of points on the surface of an object. It employs the Gauss-Newton algorithm and a few other measures to achieve very fast and highly accurate image matching. Because the detected vibrations are directly related to the sound waves, a simple model is introduced to reconstruct the original audio information of the sound waves. The proposed technique is robust and easy to implement, and its effectiveness has been verified by experiments.