Real-Time 3D Reconstruction for Collision Avoidance in Interventional Environments
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Modeling and Online Recognition of Surgical Phases Using Hidden Markov Models
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Modeling the Model Athlete: Automatic Coaching of Rowing Technique
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
On-line recognition of surgical activity for monitoring in the operating room
IAAI'08 Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3
Development of a wireless sensor glove for surgicalskills assessment
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Functional near infrared spectroscopy in novice and expert surgeons: a manifold embedding approach
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
A boosted segmentation method for surgical workflow analysis
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Modeling and segmentation of surgical workflow from laparoscopic video
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Sparse hidden markov models for surgical gesture classification and skill evaluation
IPCAI'12 Proceedings of the Third international conference on Information Processing in Computer-Assisted Interventions
Surgical gesture classification from video data
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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Laparoscopic surgery poses many different constraints to the operating surgeon, this has resulted in a slow uptake of advanced laparoscopic procedures. Traditional approaches to the assessment of surgical performance rely on prior classification of a cohort of surgeons’ technical skills for validation, which may introduce subjective bias to the outcome. In this study, Hidden Markov Models (HMMs) are used to learn surgical maneuvers from 11 subjects with mixed abilities. By using the leave-one-out method, the HMMs are trained without prior clustering subjects into different skills levels, and the output likelihood indicates the similarity of a particular subject’s motion trajectories to the group. The experimental results demonstrate the strength of the method in ranking the quality of trajectories of the subjects, highlighting its value in minimizing the subjective bias in skills assessment for minimally invasive surgery.