Real-time identification of operating room state from video
IAAI'07 Proceedings of the 19th national conference on Innovative applications of artificial intelligence - Volume 2
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
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Data-Derived Models for Segmentation with Application to Surgical Assessment and Training
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
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
HMM assessment of quality of movement trajectory in laparoscopic surgery
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Automatic detection and segmentation of robot-assisted surgical motions
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
An application-dependent framework for the recognition of high-level surgical tasks in the OR
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Detection of unsafe action from laparoscopic cholecystectomy video
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Classification of surgical processes using dynamic time warping
Journal of Biomedical Informatics
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
Intervention time prediction from surgical low-level tasks
Journal of Biomedical Informatics
Multi-site study of surgical practice in neurosurgery based on surgical process models
Journal of Biomedical Informatics
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Modeling and analyzing surgeries based on signals that are obtained automatically from the operating room (OR) is a field of recent interest. It can be valuable for analyzing and understanding surgical workflow, for skills evaluation and developing context-aware ORs. In minimally invasive surgery, laparoscopic video is easy to record but it is challenging to extract meaningful information from it. We propose a method that uses additional information about tool usage to perform a dimensionality reduction on image features. Using Canonical Correlation Analysis (CCA) a projection of a high-dimensional image feature space to a low dimensional space is obtained such that semantic information is extracted from the video. To model a surgery based on the signals in the reduced feature space two different statistical models are compared. The capability of segmenting a new surgery into phases only based on the video is evaluated. Dynamic Time Warping which strongly depends on the temporal order in combination with CCA shows the best results.