Cylindrical Echocardiographic Image Segmentation Based on 3D Deformable Models

@inproceedings{Montagnat1999CylindricalEI,
  title={Cylindrical Echocardiographic Image Segmentation Based on 3D Deformable Models},
  author={Johan Montagnat and Herv{\'e} Delingette and Gr{\'e}goire Malandain},
  booktitle={MICCAI},
  year={1999}
}
This paper presents a 3D echocardiographic image segmentation procedure based on deformable surfaces. We first propose to adapt filtering techniques to the cylindrical geometry of several 3D ultrasound image devices. Then we compare the effect of different external forces on a surface template deformation inside volumetric echocardiographic images. An original method involving region grey-level analysis along the model normal directions is described. We rely on an a priori knowledge of the… 

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References

SHOWING 1-10 OF 14 REFERENCES

Evaluating a robust contour tracker on echocardiographic sequences

On-line analysis of echocardiographic image sequences

Expert-Model Based 3 D Reconstruction of the Left Ventricle Using Transthorasic Echographic Images

TLDR
An approach based on a pre-calculated model of the displacement eld of the heart to guide the detection process in combination with active contours is proposed for the automated Left Ven-tricle reconstruction (3D+t).

Three-dimensional spatial compounding of ultrasound images

Fast surface and volume estimation from non-parallel cross-sections, for freehand 3-D ultrasound

TLDR
Two techniques for volume measurement from ultrasound B-scans are proposed, which improve surface and volume estimation from data acquired on parallel planes and are more accurate than step-section planimetry, and require fewer cross-sections, even for complex objects.

Line and boundary detection in speckle images

TLDR
It is shown that when the noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance.

Recursive filtering and edge tracking: two primary tools for 3D edge detection

Medical Image Analysis: Progress over Two Decades and the Challenges Ahead

TLDR
A look at progress in the field over the last 20 years is looked at and some of the challenges that remain for the years to come are suggested.