scholarly journals Strategies to Improve the Function, Kinematic and Implants’ Positioning of a TKA with Minimally Invasive Computer-Assisted Navigation

10.5772/27299 ◽  
2012 ◽  
Author(s):  
Nicola Biasca ◽  
Matthias Bungartz
Keyword(s):  
Minimally Invasive ◽  
Computer Assisted ◽  
Assisted Navigation

scholarly journals Application of a new percutaneous multi-function pedicle locator in minimally invasive spine surgery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaojian Liu ◽  
Hairun Liu ◽  
Yushan Wang
Keyword(s):  
Minimally Invasive ◽  
Spine Surgery ◽  
Three Dimensional ◽  
Operation Time ◽  
Minimally Invasive Spine Surgery ◽  
Computer Assisted ◽  
Assisted Navigation ◽  
Number Of Patients ◽  
Potential Benefits ◽  
Minimally Invasive Spine

AbstractIn this study, a new percutaneous multi-function pedicle locator was designed for personalized three-dimensional positioning of a pedicle in minimally invasive spine surgery (MISS) without computer-assisted navigation technology. The proposed locator was used in a number of patients during MISS, and its advantages were analyzed. Based on the position of a pedicle determined by computed tomography (CT) and fluoroscopic images of a patient, 6 lines and 2 distances were used to determine the puncture point of a pedicle screw on skin, while 2 angles were used to indicate the direction of insertion of a pedicle guide needle from the patient's body surface. The results of the proposed locator were compared with those of the conventional freehand technique in MISS. The potential benefits of using the locator included enhanced surgical accuracy, reduced operation time, alleviation of the harmful intra-operative radiation exposure, lower costs, and shortened learning curve for young orthopedists.

scholarly journals Multi-View 3D Skin Feature Recognition and Localization for Patient Tracking in Spinal Surgery Applications

2020 ◽  
Author(s):  
Francesca Manni ◽  
Marco Mamprin ◽  
Ronald Holthuizen ◽  
Caifeng Shan ◽  
Gustav Burstöm ◽  
...  
Keyword(s):  
Minimally Invasive ◽  
Feature Detection ◽  
Feature Recognition ◽  
Imaging Techniques ◽  
Ground Truth ◽  
Computer Assisted ◽  
Clinical Workflow ◽  
Localization Accuracy ◽  
Patient Tracking ◽  
Assisted Navigation

Abstract Background: Minimally invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation is increasingly used in minimally invasive surgery (MIS), but current solutions require the use of reference markers in the surgical field for both patient and instruments tracking. Purpose: To improve reliability and facilitate clinical workflow, this study proposes a new marker-free tracking framework based on skin feature recognition. Methods: Maximally Stable Extremal Regions (MSER) and Speeded Up Robust Feature (SURF) algorithms are applied for skin feature detection. The proposed tracking framework is based on a multi-camera setup for obtaining multi-view acquisitions of the surgical area. Features can then be accurately detected using MSER and SURF and afterwards localized by triangulation. The triangulation error is used for assessing the localization quality in 3D. Results: The framework was tested on a cadaver dataset and in eight clinical cases. The detected features for the entire patient datasets were found to have an overall triangulation error of 0.207 mm for MSER and 0.204 mm for SURF. The localization accuracy was compared to a system with conventional markers, serving as a ground truth. An average accuracy of 0.627 and 0.622 mm was achieved for MSER and SURF, respectively. Conclusions: This study demonstrates that skin feature localization for patient tracking in a surgical setting is feasible. The technology shows promising results in terms of detected features and localization accuracy. In the future, the framework may be further improved by exploiting extended feature processing using modern optical imaging techniques for clinical applications where patient tracking is crucial.

Image-guided minimally invasive endopancreatic surgery using a computer-assisted navigation system

2020 ◽  
Author(s):  
Philip C. Müller ◽  
Caroline Haslebacher ◽  
Daniel C. Steinemann ◽  
Beat P. Müller-Stich ◽  
Thilo Hackert ◽  
...  
Keyword(s):  
Minimally Invasive ◽  
Navigation System ◽  
Computer Assisted ◽  
Assisted Navigation ◽  
Image Guided
Sign in / Sign up

Export Citation Format

Share Document