A Real-Time 3D Laparoscopic Imaging System: Design, Method, and Validation

Sui, Congying; Wu, Jiahao; Wang, Zerui; Ma, Gan; Liu, Yunhui

doi:10.1109/tbme.2020.2968488

Cited by 14 publications

(8 citation statements)

References 42 publications

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“…Even a liquid crystal display was assumed as a flat plane specimen to evaluate the precision of a compact 3D measurement unit 40 . Similar to references, 26 , 41 , 42 the method of fitting and statistic was adopted in the present study for reconstruction precision analysis. Based on the acquired 3D point cloud, the plane fitting by a polynomial was conducted to obtain the ideal plane (R2=0.9998) as the ground truth, as shown in Fig.…”

Section: Experiments and Resultsmentioning

confidence: 99%

ArthroNavi framework: stereo endoscope-guided instrument localization for arthroscopic minimally invasive surgeries

Long,

Chi,

et al. 2023

J. Biomed. Opt.

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.SignificanceAs an example of a minimally invasive arthroscopic surgical procedure, arthroscopic osteochondral autograft transplantation (OAT) is a common option for repairing focal cartilage defects in the knee joints. Arthroscopic OAT offers considerable benefits to patients, such as less post-operative pain and shorter hospital stays. However, performing OAT arthroscopically is an extremely demanding task because the osteochondral graft harvester must remain perpendicular to the cartilage surface to avoid differences in angulation.AimWe present a practical ArthroNavi framework for instrument pose localization by combining a self-developed stereo endoscopy with electromagnetic computation, which equips surgeons with surgical navigation assistance that eases the operational constraints of arthroscopic OAT surgery.ApproachA prototype of a stereo endoscope specifically fit for a texture-less scene is introduced extensively. Then, the proposed framework employs the semi-global matching algorithm integrating the matching cubes method for real-time processing of the 3D point cloud. To address issues regarding initialization and occlusion, a displaying method based on patient tracking coordinates is proposed for intra-operative robust navigation. A geometrical constraint method that utilizes the 3D point cloud is used to compute a pose for the instrument. Finally, a hemisphere tabulation method is presented for pose accuracy evaluation.ResultsExperimental results show that our endoscope achieves 3D shape measurement with an accuracy of <730 μm. The mean error of pose localization is 15.4 deg (range of 10.3 deg to 21.3 deg; standard deviation of 3.08 deg) in our ArthroNavi method, which is within the same order of magnitude as that achieved by experienced surgeons using a freehand technique.ConclusionsThe effectiveness of the proposed ArthroNavi has been validated on a phantom femur. The potential contribution of this framework may provide a new computer-aided option for arthroscopic OAT surgery.

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Section: Experiments and Resultsmentioning

confidence: 99%

ArthroNavi framework: stereo endoscope-guided instrument localization for arthroscopic minimally invasive surgeries

Long,

Chi,

et al. 2023

J. Biomed. Opt.

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“…It evidences that the two are well-matched. To know the accuracy, the root mean square error (RMS) and the relative error (RE) are computed via Equations (4) and (5). Where do i and ds i are the depth of the one point in the reconstructed point cloud and scanned point cloud, respectively.…”

Section: Results Of 3d Stitchingmentioning

confidence: 99%

“…There are also some studies on the 3D reconstruction of organs based on structured light [5]. However, structured light devices are complex and difficult to be used in a clinic setting.…”

Section: Discussionmentioning

confidence: 99%

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Three-Dimensional Stitching of Binocular Endoscopic Images Based on Feature Points

Zhou

Yuan

et al. 2021

Photonics

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There are shortcomings of binocular endoscope three-dimensional (3D) reconstruction in the conventional algorithm, such as low accuracy, small field of view, and loss of scale information. To address these problems, aiming at the specific scenes of stomach organs, a method of 3D endoscopic image stitching based on feature points is proposed. The left and right images are acquired by moving the endoscope and converting them into point clouds by binocular matching. They are then preprocessed to compensate for the errors caused by the scene characteristics such as uneven illumination and weak texture. The camera pose changes are estimated by detecting and matching the feature points of adjacent left images. Finally, based on the calculated transformation matrix, point cloud registration is carried out by the iterative closest point (ICP) algorithm, and the 3D dense reconstruction of the whole gastric organ is realized. The results show that the root mean square error is 2.07 mm, and the endoscopic field of view is expanded by 2.20 times, increasing the observation range. Compared with the conventional methods, it does not only preserve the organ scale information but also makes the scene much denser, which is convenient for doctors to measure the target areas, such as lesions, in 3D. These improvements will help improve the accuracy and efficiency of diagnosis.

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“…[12,13], or a high-resolution fiber bundle, e.g. [14,15]. In these studies, the surface height map was extracted using phaseshifting fringe-projection profilometry, which allows fast and precise full-field shape measurement.…”

Section: Introductionmentioning

confidence: 99%

A calibrated 3D dual-barrel otoendoscope based on fringe-projection profilometry

Muyshondt¹,

Jeught²,

Dirckx³

2022

Optics and Lasers in Engineering

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A Real-Time 3D Laparoscopic Imaging System: Design, Method, and Validation

Cited by 14 publications

References 42 publications

ArthroNavi framework: stereo endoscope-guided instrument localization for arthroscopic minimally invasive surgeries

ArthroNavi framework: stereo endoscope-guided instrument localization for arthroscopic minimally invasive surgeries

Three-Dimensional Stitching of Binocular Endoscopic Images Based on Feature Points

A calibrated 3D dual-barrel otoendoscope based on fringe-projection profilometry

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