Real-time segmentation of surgical instruments inside the abdominal cavity using a joint hue saturation color feature

2005 ◽  
Vol 11 (5-6) ◽  
pp. 429-442 ◽  
Author(s):  
C. Doignon ◽  
P. Graebling ◽  
M. de Mathelin
Keyword(s):  
Real Time ◽  
Abdominal Cavity ◽  
Surgical Instruments ◽  
Color Feature ◽  
Time Segmentation

scholarly journals Attention-Guided Lightweight Network for Real-Time Segmentation of Robotic Surgical Instruments

2020 ◽  
Author(s):  
Zhen-Liang Ni ◽  
Gui-Bin Bian ◽  
Zeng-Guang Hou ◽  
Xiao-Hu Zhou ◽  
Xiao-Liang Xie ◽  
...  
Keyword(s):  
Real Time ◽  
Surgical Instruments ◽  
Time Segmentation

A study of real-time simulation of liver of virtual surgical robot based on biologically position-based dynamic model

2021 ◽  
pp. 1-16
Author(s):  
Dan Luo ◽  
Yu Zhang ◽  
Jia Li ◽  
Jisheng Li
Keyword(s):  
Soft Tissue ◽  
Real Time ◽  
Surgical Instruments ◽  
Organic Polymer ◽  
Tetrahedral Mesh ◽  
Virtual Surgery ◽  
Constraint Force ◽  
Real Time Simulation ◽  
Time Simulation ◽  
Spring Force

Virtual surgery robot can accurately modeling of surgical instruments and human organs, and realistic simulation of various surgical phenomena such as deformation of organic tissues, surgery simulation system can provide operators with reusable virtual training and simulation environment. To meet the requirement of virtual surgery robot for the authenticity and real-time of soft tissue deformation and surgical simulation in liver surgery, a new method is proposed to simulate the deformation of soft tissue. This method combines the spring force, the external force of the system, and the constraint force produced by the constraint function of the position-based dynamics. Based on the position-based dynamics, an improved three-parameter mass-spring model is added. In the calculation of the elastic force, the nonlinearity and viscoelasticity of the soft tissue are introduced, and the joint force of the constraint projection process and the constraint force of the position-based dynamics is used to modify mass points movement. The method of position-based dynamics based on biological characteristics, not only considers the biomechanical properties of biological soft tissue as an organic polymer such as viscoelasticity, nonlinearity, and incompressibility but also retains the rapidity and stability of the position based dynamic method. Through the simulation data, the optimal side length of tetrahedral mesh in the improved three-parameter model is obtained, and the physical properties of the model are proved. The real-time simulation of the liver and other organs is completed by using the Geomagic touch force feedback device, which proves the practicability and effectiveness of this method.

Three-dimensional Force Perception of Robotic Bipolar Forceps for Brain Tumor Resection

2021 ◽  
Author(s):  
Xiu-Heng Zhang ◽  
Heng Zhang ◽  
Zhen Li ◽  
Gui-Bin Bian
Keyword(s):  
Brain Tumor ◽  
Real Time ◽  
Force Measurement ◽  
Measurement Techniques ◽  
Tumor Resection ◽  
Three Dimensional ◽  
Contact Forces ◽  
Surgical Instruments ◽  
Force Perception ◽  
Brain Tumor Resection

Abstract Three-dimensional force perception is critically important in the enhancement of human force perception to minimize brain injuries resulting from excessive forces applied by surgical instruments in robot-assisted brain tumor resection. And surgeons are not responsive enough to interpret tool-tissue interaction forces. In previous studies, various force measurement techniques have been published. In neurosurgical scenarios, there are still some drawbacks to these presented approaches to forces perception. Because of the narrow, and slim configuration of bipolar forceps, three-dimensional contact forces on forceps tips is not easy to be traced in real-time. Five fundamental acts of handling bipolar forceps are poking, opposing, pressing, opening, and closing. The first three acts independently correspond to the axial force of z, x, y. So, in this paper, typical interactions between bipolar forceps and brain tissues have been analyzed. A three-dimensional force perception technique to collect force data on bipolar forceps tips by installing three Fiber Bragg Grating Sensors (FBGs) on each prong of bipolar forceps in real-time is proposed. Experiments using a tele-neurosurgical robot were performed on an in-vitro pig brain. In the experiments, three-dimensional forces were tracked in real-time. It is possible to experience forces at a minimum of 0.01 N. The three-dimensional force perception range is 0-4 N. The calibrating resolution on x, y, and z, is 0.01, 0.03, 0.1 N, separately. According to our observation, the measurement accuracy precision is over 95%.

scholarly journals Development of detection method for automatic hemostasis using machine learning with abdominal cavity irrigation

2020 ◽  
Vol 7 (7) ◽  
pp. 2103
Author(s):  
Yoshihisa Matsunaga ◽  
Ryoichi Nakamura
Keyword(s):  
Machine Learning ◽  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Abdominal Cavity ◽  
Training Dataset ◽  
Support Vector ◽  
Processing Cost ◽  
Surgical Field

Background: Abdominal cavity irrigation is a more minimally invasive surgery than that using a gas. Minimally invasive surgery improves the quality of life of patients; however, it demands higher skills from the doctors. Therefore, the study aimed to reduce the burden by assisting and automating the hemostatic procedure a highly frequent procedure by taking advantage of the clearness of the endoscopic images and continuous bleeding point observations in the liquid. We aimed to construct a method for detecting organs, bleeding sites, and hemostasis regions.Methods: We developed a method to perform real-time detection based on machine learning using laparoscopic videos. Our training dataset was prepared from three experiments in pigs. Linear support vector machine was applied using new color feature descriptors. In the verification of the accuracy of the classifier, we performed five-part cross-validation. Classification processing time was measured to verify the real-time property. Furthermore, we visualized the time series class change of the surgical field during the hemostatic procedure.Results: The accuracy of our classifier was 98.3% and the processing cost to perform real-time was enough. Furthermore, it was conceivable to quantitatively indicate the completion of the hemostatic procedure based on the changes in the bleeding region by ablation and the hemostasis regions by tissue coagulation.Conclusions: The organs, bleeding sites, and hemostasis regions classification was useful for assisting and automating the hemostatic procedure in the liquid. Our method can be adapted to more hemostatic procedures. 

scholarly journals Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking

2017 ◽  
pp. 84-95 ◽  
Author(s):  
Luis C. García-Peraza-Herrera ◽  
Wenqi Li ◽  
Caspar Gruijthuijsen ◽  
Alain Devreker ◽  
George Attilakos ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Surgical Tools ◽  
Time Segmentation

Real-Time Segmentation of Surgical Tools and Needle Using a Mobile-U-Net

2021 ◽  
Author(s):  
Jakob Kristian Holm Andersen ◽  
Kim Lindberg Schwaner ◽  
Thiusius Rajeeth Savarimuthu
Keyword(s):  
Real Time ◽  
Surgical Tools ◽  
Time Segmentation
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