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Fast and Fully Automatic Left Ventricular Segmentation and Tracking in Echocardiography Using Shape-Based B-Spline Explicit Active Surfaces

Pedrosa, Joao (author)
Katholieke University of Leuven, Belgium
Queiros, Sandro (author)
Katholieke University of Leuven, Belgium; University of Minho, Portugal; University of Minho, Portugal
Bernard, Olivier (author)
University of Lyon 1, France
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Engvall, Jan (author)
Linköpings universitet,Avdelningen för kardiovaskulär medicin,Medicinska fakulteten,Region Östergötland, Fysiologiska kliniken US
Edvardsen, Thor (author)
University of Oslo, Norway; Oslo University Hospital, Norway
Nagel, Eike (author)
University Hospital Frankfurt Main, Germany
Dhooge, Jan (author)
Katholieke University of Leuven, Belgium
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 (creator_code:org_t)
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2017
2017
English.
In: IEEE Transactions on Medical Imaging. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0278-0062 .- 1558-254X. ; 36:11, s. 2287-2296
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Cardiac volume/function assessment remains a critical step in daily cardiology, and 3-D ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation is, however, a challenging task due to the artifacts and low contrast-to-noise ratio of ultrasound imaging. In this paper, a fast and fully automatic framework for the full-cycle endocardial left ventricle segmentation is proposed. This approach couples the advantages of the B-spline explicit active surfaces framework, a purely image information approach, to those of statistical shape models to give prior information about the expected shape for an accurate segmentation. The segmentation is propagated throughout the heart cycle using a localized anatomical affine optical flow. It is shown that this approach not only outperforms other state-of-the-art methods in terms of distance metrics with a mean average distances of 1.81 +/- 0.59 and 1.98 +/- 0.66 mm at end-diastole and end-systole, respectively, but is computationally efficient (in average 11 s per 4-D image) and fully automatic.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Keyword

3-D echocardiography; left ventricle segmentation; B-spline explicit active surfaces; statistical shape model; localized anatomical affine optical flow

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