Real-time robust individual X point localization for stereoscopic tracking

Wang, Junchen; Ji, Xuquan; Zhang, Xiaohui; Sun, Zhen; Wang, Tianmiao

doi:10.1016/j.patrec.2018.07.002

Cited by 11 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The videometric tracker integrated by the Remebot robotic system is a commercially available third-generation stereoscopic optical tracking product (Sánchez-Margallo et al, 2014;Choi et al, 2019). The MicronTracker (ClaroNav, Canada) has been used in rigid tissue surgical navigation, such as orthopedic surgery (Wang et al, 2018) [other than for neurosurgery (Wei et al, 2011)], maxillary orthognathic surgery (Choi et al, 2019) and laparoscopic surgery (Sánchez-Margallo et al, 2014). Tracked objects are marked with a visible target pattern which consists of high-contrast black-white interleaved regions called X points (Figure 2).…”

Section: Surgical Proceduresmentioning

confidence: 99%

Application of the robot-assisted implantation in deep brain stimulation

Liu

Yang

et al. 2022

Front. Neurorobot.

View full text Add to dashboard Cite

IntroductionThis work aims to assess the accuracy of robotic assistance guided by a videometric tracker in deep brain stimulation (DBS).MethodsWe retrospectively reviewed a total of 30 DBS electrode implantations, assisted by the Remebot robotic system, with a novel frameless videometric registration workflow. Then we selected 30 PD patients who used stereotactic frame surgery to implant electrodes during the same period. For each electrode, accuracy was assessed using radial and axial error.ResultsThe average radial error of the robot-assisted electrode implantation was 1.28 ± 0.36 mm, and the average axial error was 1.20 ± 0.40 mm. No deaths or associated hemorrhages, infections or poor incision healing occurred.ConclusionRobot-assisted implantation guided by a videometric tracker is accurate and safe.

show abstract

Section: Surgical Proceduresmentioning

confidence: 99%

Application of the robot-assisted implantation in deep brain stimulation

Liu

Yang

et al. 2022

Front. Neurorobot.

View full text Add to dashboard Cite

show abstract

“…The problems posed by the line of sight between the camera and conventional infrared markers represent another non‐negligible drawback during optical navigation. However, the Remebot surgical robot integrates an available third‐generation stereoscopic optical tracking camera, 20,21 which has been used during the surgical navigation of rigid tissues, such as during neurosurgical and orthopedic surgeries, 22 maxillary orthognathic surgery, and laparoscopic surgery. Compared with second‐generation optical trackers, the most commonly used optical systems, which emit infrared light and apply retro‐reflective markers, this camera is fully passive and uses available visible light illumination to detect and track objects of interest, much like humans do, by triangulating 3D poses between two video cameras with overlapping projections.…”

Section: Discussionmentioning

confidence: 99%

A new multimodal, image‐guided, robot‐assisted, interstitial brachytherapy for the treatment of head and neck tumors–A preliminary study

Meng¹,

Xue²,

Qiao³

et al. 2020

Robotics Computer Surgery

View full text Add to dashboard Cite

Background: Interstitial brachytherapy (BT) is becoming an accepted treatment option for head and neck cancer patients for whom surgery poses high risks. Multimodal, image-guided, robotic surgery has the potential to allow precise seed implantation into tumors. Our aim was to introduce a new multimodal, image-guided surgical robot during the performance of interstitial BT for the treatment of tumors in the head and neck regions. Methods: Clinical data for three patients were analyzed, retrospectively; patients had received 125 I seed implantations from July 2019 to October 2019. Multimodal, image-guided, robotic surgery was performed in all patients. Postoperative computed tomography data were imported to software to evaluate the accuracy of the seed position and the operation times. Results: The mean placement error of the 125 I seed was 1.9 ± 0.74 mm. The mean operation time is 47 minutes. Conclusion: The experimental results showed that the Remebot has promise for use during BT for the head and neck.

show abstract

“…Gauss noise from s = 0 to s = 0:24 with interval Ds = 0:04 was added to the image. Equations (10) and (11) are utilized to measure the X-corner location and orientation error…”

Section: Tests With Synthetic Imagesmentioning

confidence: 99%

“…3,4 Unfortunately, as a commercial product, its algorithm for X-corner detection has not been made public yet. But for customizing task-specific application, 10 an efficient and robust X-corner detection framework is implemental.…”

Section: Introductionmentioning

confidence: 99%

A fast X-corner detection method based on block-search strategy

Cai

Wang

et al. 2019

Advances in Mechanical Engineering

Self Cite

View full text Add to dashboard Cite

In order to detect X-corner (or X-point) features more accurately and apace, this article presents a novel and fast detection method based on block-by-block search strategy. Unlike general pixel-by-pixel searching method, the sampling window is first moved along the image block-by-block to find the X-corner candidates rapidly keeping in view the fourstep and min-step-distance constraints. During the motion, some overlap is kept between the adjacent sampling windows in order to ensure that all X-corners could have a chance to reside inside, avoiding the possibility of that some Xcorners may locate on the edge. Moreover, labeling technology is adopted to prevent duplicate candidates. After the collection of X-corner candidates, the neighborhood variance and centrosymmetry constraints are used to exclude outliers, and the intersection lines is calculated as the sub-pixel position of true X-corner. The experimental results using synthetic and real images show that the presented method approximately takes just about 13 ms to detect 52 X-corners in an image size of 1024 3 768 on a computer having Intel Core i3 CPU at 3.6 GHz and 4GB RAM. The proposed method has faster detection speed compared with the latest methods such as ChESS, SC, and Micron Tracker system while possessing the same or higher detection precision.

show abstract

Real-time robust individual X point localization for stereoscopic tracking

Cited by 11 publications

References 16 publications

Application of the robot-assisted implantation in deep brain stimulation

Application of the robot-assisted implantation in deep brain stimulation

A new multimodal, image‐guided, robot‐assisted, interstitial brachytherapy for the treatment of head and neck tumors–A preliminary study

A fast X-corner detection method based on block-search strategy

Contact Info

Product

Resources

About