April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Indexing of cataract surgery video by content based video retrieval (CBVR).
Author Affiliations & Notes
  • MARTIANO David
    Ophthalmology Department, CHRU BREST, Brest, France
    LaTIM, INSERM UMR 1101, BREST, France
  • Katia Charriere
    Ophthalmology Department, CHRU BREST, Brest, France
    TELECOM BRETAGNE, BREST, France
  • Lamard Mathieu
    LaTIM, INSERM UMR 1101, BREST, France
    UBO, Brest, France
  • Quellec Gwenole
    Ophthalmology Department, CHRU BREST, Brest, France
    TELECOM BRETAGNE, BREST, France
  • Cazuguel Guy
    LaTIM, INSERM UMR 1101, BREST, France
    TELECOM BRETAGNE, BREST, France
  • Beatrice Cochener
    Ophthalmology Department, CHRU BREST, Brest, France
    LaTIM, INSERM UMR 1101, BREST, France
  • Footnotes
    Commercial Relationships MARTIANO David, None; Katia Charriere, None; Lamard Mathieu, None; Quellec Gwenole, None; Cazuguel Guy, None; Beatrice Cochener, ALCON (C), ALLERGAN (C), B&L (C), PHYSIOL (C), RMO (C), THEA (C), ZEISS (F)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 4845. doi:https://doi.org/
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      MARTIANO David, Katia Charriere, Lamard Mathieu, Quellec Gwenole, Cazuguel Guy, Beatrice Cochener; Indexing of cataract surgery video by content based video retrieval (CBVR).. Invest. Ophthalmol. Vis. Sci. 2014;55(13):4845. doi: https://doi.org/.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose: Many surgical computer-aided projects ( CAD ) have emerged in recent years, but none interested in cataract surgery . The aim of our study was to develop a method able to recognize in real time the video stream , surgical phases clearly identified and thus to classify them in a database .

Methods: Over a period of 2 years, we have adopted a first series of 60 videos of cataract surgery , performed by six different surgeons acquired DV format with a resolution of 720x276 pixels. The operating parameters were recorded in postoperative dedicated form. Our first method characterized videos in 9 phases : incision , OVD injection, capsulorhexis , hydrodissection , phacoemulsification , epi - core implementation , OVD aspiration and closure. We developed specifically for this study , a novel characterization method using a granular system at several levels. To recognize in real time during the surgical phase , we used search algorithms for video content. The parameters studied were primarily based on visual content ( movement , shapes, contours , colors, textures ) . Finally , we used the calculation of the area under the ROC curve for the quantification measure of the quality of the results of our method on each of these phases .

Results: The average video length was 15.25 + / - 7 minutes [ 10.05-28 ] . 8 videos were atypical ( implemented iris hooks , toric IOL) . The mean area under the curve was 0.806 + / - 0.1 [ 0563-0937 ] for the analysis of complete sequences . A gain of 8% was found after improvement of the method using the measurement granularity , which has overcome the overlapping phases and periods of inactivity : 0.887 + / - 0.1 [ 0612-0941 ] .

Conclusions: We chose to measure granularity in 4 different levels: stage , action, gesture and tool. These recognition systems surgical tasks , whether in level or phases activity level , appear as a significant progress towards the construction of smart systems for surgery. Our method gives good quality results for sequencing our database video cataract surgery. And apart from some interest to have a database by automated grading , we can imagine the development of a device to support the initiation of surgical novice. In this way, real-time applications for intra-operative assistance may be developped , for example by allowing real time to know which information needs to be showned to the surgeon for the task performed ..

Keywords: 549 image processing • 445 cataract • 713 shape, form, contour, object perception  
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×