Coding and information theory (2nd ed.)
Coding and information theory (2nd ed.)
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
IEEE Transactions on Computers
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
Automatic phases recognition in pituitary surgeries by microscope images classification
IPCAI'10 Proceedings of the First international conference on Information processing in computer-assisted interventions
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
Surgical phases detection from microscope videos by combining SVM and HMM
MCV'10 Proceedings of the 2010 international MICCAI conference on Medical computer vision: recognition techniques and applications in medical imaging
Discovery of high-level tasks in the operating room
Journal of Biomedical Informatics
Recovery of surgical workflow without explicit models
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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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Surgical process analysis and modeling is a recent and important topic aiming at introducing a new generation of computer-assisted surgical systems. Among all of the techniques already in use for extracting data from the Operating Room, the use of image videos allows automating the surgeons' assistance without altering the surgical routine. We proposed in this paper an application-dependent framework able to automatically extract the phases of the surgery only by using microscope videos as input data and that can be adaptable to different surgical specialties. First, four distinct types of classifiers based on image processing were implemented to extract visual cues from video frames. Each of these classifiers was related to one kind of visual cue: visual cues recognizable through color were detected with a color histogram approach, for shape-oriented visual cues we trained a Haar classifier, for texture-oriented visual cues we used a bag-of-word approach with SIFT descriptors, and for all other visual cues we used a classical image classification approach including a feature extraction, selection, and a supervised classification. The extraction of this semantic vector for each video frame then permitted to classify time series using either Hidden Markov Model or Dynamic Time Warping algorithms. The framework was validated on cataract surgeries, obtaining accuracies of 95%.