• DocumentCode
    1825673
  • Title

    AutoMPR: Automatic detection of standard planes in 3D echocardiography

  • Author

    Lu, Xiaoguang ; Georgescu, Bogdan ; Zheng, Yefeng ; Otsuki, Joanne ; Comaniciu, Dorin

  • Author_Institution
    Siemens Corp. Res., Princeton, NJ
  • fYear
    2008
  • fDate
    14-17 May 2008
  • Firstpage
    1279
  • Lastpage
    1282
  • Abstract
    3D echocardiography is one of the emerging real-time imaging modalities that is increasingly used in clinical practice to assess cardiac functions. It provides a more complete heart representation for evaluation in comparison to conventional 2D echocardiography. However, one of the drawbacks is the time it takes clinicians to navigate the 3D volumes to the anatomy of interest and to obtain standardized views that are similar to the 2D acquisitions. We propose an automated supervised learning method to detect standard multiplanar reformatted planes (MPRs) from a 3D echocardiographic volume. Extensive evaluations on a database of 326 volumes show performance comparable to intra-user variability and the execution time of the algorithm is about 2 seconds.
  • Keywords
    echocardiography; learning (artificial intelligence); medical computing; 3D echocardiography; AUTOMPR; automated supervised learning; automatic standard plane detection; cardiac function; heart representation; intra-user variability; real-time imaging modality; standard multiplanar reformatted planes; Anatomy; Biomedical imaging; Echocardiography; Heart; Image analysis; Image quality; Image reconstruction; Information analysis; Navigation; Robustness; Three-dimensional echocardiography; multiplanar reformatted/reconstruction (MPR); standard views;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4244-2002-5
  • Electronic_ISBN
    978-1-4244-2003-2
  • Type

    conf

  • DOI
    10.1109/ISBI.2008.4541237
  • Filename
    4541237