Prior-shape-based segmentation of various objects in ultrasound images after speckle-reduction using level-set-based curvature evolution

Joyoni Dey; Dennis A. Tighe M.D.; Gopal Vijayaraghavan M.D.; Vikramjit Mitra; Peder Pedersen

doi:10.1117/12.655037

15 March 2006 Prior-shape-based segmentation of various objects in ultrasound images after speckle-reduction using level-set based curvature evolution

Joyoni Dey, Dennis A. Tighe M.D., Gopal Vijayaraghavan M.D., Vikramjit Mitra, Peder Pedersen

Author Affiliations +

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61444P (2006) https://doi.org/10.1117/12.655037
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Medical ultrasound images are noisy with speckle, acoustic noise and other artifacts. Reduction of speckle in particular is useful for CAD algorithms. We use two algorithms, namely, mean curvature evolution of the ultrasound image surface and a variation of the mean-curvature flow, to reduce speckle. The premise is that when we view the ultrasound image as a surface, the speckle appears as a high-curvature jagged layer over the true objects intensities and will reduce quickly on curvature evolution. We compare the two speckle reduction algorithms. We apply the speckle reduction to an image of a cyst and a 4-chamber view of the heart. We show significant, if not complete, speckle reduction, while keeping the relevant organ boundaries intact. On the speckle-reduced images, we apply a segmentation algorithm to detect objects. The segmentation algorithm is two-stepped. In the first step we choose a prior-shape and optimize the pose parameters to maximize the edge-pixels the curve falls into, using gradient ascent. In the second step, a radial motion is used to draw the contour points to the local-edges. We apply the algorithm on a cyst and obtain satisfactory results. We compare the total area inside the boundary output of our segmentation algorithm and to the total area covered by a hand-drawn boundary of the cyst, and the ratio is about 97%.

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Joyoni Dey, Dennis A. Tighe M.D., Gopal Vijayaraghavan M.D., Vikramjit Mitra, and Peder Pedersen "Prior-shape-based segmentation of various objects in ultrasound images after speckle-reduction using level-set based curvature evolution", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61444P (15 March 2006); https://doi.org/10.1117/12.655037

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