Automatic phases recognition in pituitary surgeries by microscope images classification

Authors:
Florent Lalys;Laurent Riffaud;Xavier Morandi;Pierre Jannin
Affiliations:
INSERM, Faculty of Medicine, Rennes, France and INRIA, Rennes, France and University of Rennes I, CNRS, UMR, IRISA, Rennes, France;Department of Neurosurgery, Pontchaillou University Hospital, Rennes, France;INSERM, Faculty of Medicine, Rennes, France and INRIA, Rennes, France and University of Rennes I, CNRS, UMR, IRISA, Rennes, France and Department of Neurosurgery, Pontchaillou University Hospital, ...;INSERM, Faculty of Medicine, Rennes, France and INRIA, Rennes, France and University of Rennes I, CNRS, UMR, IRISA, Rennes, France
Venue:
IPCAI'10 Proceedings of the First international conference on Information processing in computer-assisted interventions
Year:
2010

Citing 8
Cited 2

Content-Based Image Retrieval at the End of the Early Years

IEEE Transactions on Pattern Analysis and Machine Intelligence
On the algorithmic implementation of multiclass kernel-based vector machines

The Journal of Machine Learning Research
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Discrete Cosine Transfom

IEEE Transactions on Computers
Segmentation and 3D Reconstruction Approaches for the Design of Laparoscopic Augmented Reality Environments

ISBMS '08 Proceedings of the 4th international symposium on Biomedical Simulation
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
Eye-gaze driven surgical workflow segmentation

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

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
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

Quantified Score

Hi-index	0.00

Visualization

Abstract

The segmentation of the surgical workflow might be helpful for providing context-sensitive user interfaces, or generating automatic report. Our approach focused on the automatic recognition of surgical phases by microscope image classification. Our workflow, including images features extraction, image database labelisation, Principal Component Analysis (PCA) transformation and 10-fold cross-validation studies was performed on a specific type of neurosurgical intervention, the pituitary surgery. Six phases were defined by an expert for this type of intervention. We thus assessed machine learning algorithms along with the data dimension reduction. We finally kept 40 features from the PCA and found a best correct classification rate of the surgical phases of 82% with the multiclass Support Vector Machine.