Contour Determination in Ultrasound Medical Images Using Interacting Multiple Model Probabilistic Data Association Filter

Konstantinova, Pavlina; Adam, Dan; Angelova, Donka; Behar, V.

doi:10.1007/978-3-540-70942-8_76

Cited by 2 publications

(2 citation statements)

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“…The correct interpretation of the image data, namely the measurement formation process, has a great importance for the segmentation qual- ity in this Bayesian context. Our experiments show, that the edge detection algorithm, proposed in [1,2], is an excellent procedure, providing accurate results in almost all studied real and simulated images [19]. In [2], the smoothing capabilities of the PDA procedure (by calculating one weighted measurement from N c edges with maximum magnitudes) provide a smooth contour estimate.…”

Section: Segmentation Resultsmentioning

confidence: 79%

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Contour segmentation in 2D ultrasound medical images with particle filtering

Angelova

Mihaylova

2010

Machine Vision and Applications

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-Object segmentation in medical images is an actively investigated research area. Segmentation techniques are a valuable tool in medical diagnostics for cancer tumors and cysts, for planning surgery operations and other medical treatment. In this paper a Monte Carlo algorithm for extracting lesion contours in ultrasound medical images is proposed. An efficient multiple model particle filter for progressive contour growing (tracking) from a starting point is developed, accounting for convex, non-circular forms of delineated contour areas. The driving idea of the proposed particle filter consists in the incorporation of different image intensity inside and outside the contour into the filter likelihood function. The filter employs image intensity gradients as measurements and requires information about four manually selected points: a seed point, a starting point, arbitrarily selected on the contour, and two additional points, bounding the measurement formation area around the contour. The filter performance is studied by segmenting contours from a number of real and simulated ultrasound medical images. Accurate contour segmentation is achieved with the proposed approach in ultrasound images with a high level of speckle noise.

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Section: Segmentation Resultsmentioning

confidence: 79%

“…The ultrasound simulation package "Field II" [18] provides an excellent tool for testing newly developed ultrasound signal processing and segmentation algorithms. By means of "Field II", images with complex contours are generated in [19], Fig. 6(a).…”

Section: Segmentation Resultsmentioning

confidence: 99%