TY - GEN
T1 - VR training system for endoscopic surgery robot
T2 - 6th International Workshop on Augmented Environments for Computer-Assisted Interventions, AE-CAI 2011, Held in Conjunction with the Medical Image Computing and Computer-Assisted Interventions, MICCAI 2011
AU - Suzuki, Naoki
AU - Hattori, Asaki
AU - Ieiri, Satoshi
AU - Tomikawa, Morimasa
AU - Kenmotsu, Hajime
AU - Hashizume, Makoto
PY - 2012/10/22
Y1 - 2012/10/22
N2 - Our research group is currently developing an endoscopic surgical robot for digestive organs. In the current study, we sought to train surgeons to manipulate the system we are developing for clinical applications. To this end, we are developing a training system with the same interface as the real system, so that surgeons in training can practice basic manipulations and surgical techniques using organ models. To learn the basic manipulations of the system, we emphasized training the surgeon to operate the robotic arms, as this is the biggest difference from the conventional surgical techniques. We set up several types of tasks for the trainee, so that a beginner trainee could get used to operating the robot arms of the system. We developed a surgical training method using a stomach model reconstructed from MRI data sets. In addition to basic surgical techniques such as grabbing, lifting and cutting open soft tissue with the robot arm, we enabled the training system to perform techniques necessary for the surgical system, such as delivering water to the surgical field in case of bleeding, and clipping of incision sites. We added a function to record the performance of the trainee, enabling the system to analyze changes of the surgical field and robot arms in four dimensions during training.
AB - Our research group is currently developing an endoscopic surgical robot for digestive organs. In the current study, we sought to train surgeons to manipulate the system we are developing for clinical applications. To this end, we are developing a training system with the same interface as the real system, so that surgeons in training can practice basic manipulations and surgical techniques using organ models. To learn the basic manipulations of the system, we emphasized training the surgeon to operate the robotic arms, as this is the biggest difference from the conventional surgical techniques. We set up several types of tasks for the trainee, so that a beginner trainee could get used to operating the robot arms of the system. We developed a surgical training method using a stomach model reconstructed from MRI data sets. In addition to basic surgical techniques such as grabbing, lifting and cutting open soft tissue with the robot arm, we enabled the training system to perform techniques necessary for the surgical system, such as delivering water to the surgical field in case of bleeding, and clipping of incision sites. We added a function to record the performance of the trainee, enabling the system to analyze changes of the surgical field and robot arms in four dimensions during training.
UR - http://www.scopus.com/inward/record.url?scp=84867529540&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867529540&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-32630-1_12
DO - 10.1007/978-3-642-32630-1_12
M3 - Conference contribution
AN - SCOPUS:84867529540
SN - 9783642326295
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 117
EP - 129
BT - Augmented Environments for Computer-Assisted Interventions - 6th International Workshop, AE-CAI 2011, Held in Conjunction with MICCAI 2011, Revised Selected Papers
Y2 - 22 September 2011 through 22 September 2011
ER -