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Surgical Phases Detection from Microscope Videos by Combining SVM and HMM

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Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging (MCV 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6533))

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Abstract

In order to better understand and describe surgical procedures by surgical process models, the field of workflow segmentation has recently emerged. It aims to recognize high-level surgical tasks in the Operating Room, with the help of sensors or human-based systems. Our approach focused on the automatic recognition of surgical phases by microscope images analysis. We used a hybrid method that combined Support Vector Machine and discrete Hidden Markov Model. We first performed features extraction and selection on surgical microscope frames to create an image database. SVMs were trained to extract surgical scene information, and then outputs were used as observations for training a discrete HMM. Our framework was tested on pituitary surgery, where six phases were identified by neurosurgeons. Cross-validation studies permitted to find a percentage of detected phases of 93% that will allow the use of the system in clinical applications such as post-operative videos indexation.

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Author information

Authors and Affiliations

  1. U746, Faculté de Médecine CS 34317, INSERM, F-35043, Rennes Cedex, France

    Florent Lalys, Xavier Morandi & Pierre Jannin

  2. VisAGeS Unité/Projet, INRIA, F-35042, Rennes, France

    Florent Lalys, Xavier Morandi & Pierre Jannin

  3. CNRS, UMR 6074, IRISA, University of Rennes I, F-35042, Rennes, France

    Florent Lalys, Xavier Morandi & Pierre Jannin

  4. Department of Neurosurgery, Pontchaillou University Hospital, F-35043, Rennes, France

    Laurent Riffaud & Xavier Morandi

Authors
  1. Florent Lalys
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  2. Laurent Riffaud
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  3. Xavier Morandi
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  4. Pierre Jannin
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Editor information

Editors and Affiliations

  1. Computer Science and Artificial Intelligence Laboratory, MIT, USA

    Bjoern Menze

  2. CSAIL - Computer Science and Artificial Intelligence Laboratory, MIT, 02139, Cambridge, MA, USA

    Georg Langs

  3. Laboratory of Neuroimaging, University of California, Los Angeles

    Zhuowen Tu

  4. Machine Learning and Perception Group, Microsoft Research Cambridge, UK

    Antonio Criminisi

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© 2011 Springer-Verlag Berlin Heidelberg

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Lalys, F., Riffaud, L., Morandi, X., Jannin, P. (2011). Surgical Phases Detection from Microscope Videos by Combining SVM and HMM. In: Menze, B., Langs, G., Tu, Z., Criminisi, A. (eds) Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging. MCV 2010. Lecture Notes in Computer Science, vol 6533. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18421-5_6

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  • DOI: https://doi.org/10.1007/978-3-642-18421-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-18420-8

  • Online ISBN: 978-3-642-18421-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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