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Alternative parametric boundary reconstruction method for biomedical imaging.

Kolibal J, Howard D - J. Biomed. Biotechnol. (2008)

Bottom Line: Determining the outline or boundary contour of a two-dimensional object, or the surface of a three-dimensional object poses difficulties particularly when there is substantial measurement noise or uncertainty.The technique is applied to parametric boundary data and has potential applications in biomedical imaging.It should be considered as one of several techniques to improve the visualization of images.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, College of Science and Technology, The University of Southern Mississippi, Hattiesburg, MS 39406-0001, USA. joseph.kolibal@usm.edu

ABSTRACT
Determining the outline or boundary contour of a two-dimensional object, or the surface of a three-dimensional object poses difficulties particularly when there is substantial measurement noise or uncertainty. By adapting the mathematical approach of stochastic function recovery to this task, it is possible to obtain usable estimates for these boundaries, even in the presence of large amounts of noise. The technique is applied to parametric boundary data and has potential applications in biomedical imaging. It should be considered as one of several techniques to improve the visualization of images.

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Related in: MedlinePlus

Recovery of the boundary of disk specified by 12 points, starting at (1, 0) on the x-axis, and moving counterclockwise around the circle. Note that in the circle in (a) the boundary of the recovered disk isapproximated with σB = 0.001 using B100,12v,resulting in the inscribed disk, while in (b) the boundary is constructed using approximate interpolation using σA = σB = 0.001 and applying B100,12A12,12Iv.
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fig1: Recovery of the boundary of disk specified by 12 points, starting at (1, 0) on the x-axis, and moving counterclockwise around the circle. Note that in the circle in (a) the boundary of the recovered disk isapproximated with σB = 0.001 using B100,12v,resulting in the inscribed disk, while in (b) the boundary is constructed using approximate interpolation using σA = σB = 0.001 and applying B100,12A12,12Iv.

Mentions: We begin by applying the process to the recovery of the boundary of a disk defined parametrically by 12 uniformly distributedpoints with no random errors in the data as shown in Figure 1. The figureclearly illustrates the aforementioned difficulty of attempting to approximate(smooth parametric data).


Alternative parametric boundary reconstruction method for biomedical imaging.

Kolibal J, Howard D - J. Biomed. Biotechnol. (2008)

Recovery of the boundary of disk specified by 12 points, starting at (1, 0) on the x-axis, and moving counterclockwise around the circle. Note that in the circle in (a) the boundary of the recovered disk isapproximated with σB = 0.001 using B100,12v,resulting in the inscribed disk, while in (b) the boundary is constructed using approximate interpolation using σA = σB = 0.001 and applying B100,12A12,12Iv.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2366076&req=5

fig1: Recovery of the boundary of disk specified by 12 points, starting at (1, 0) on the x-axis, and moving counterclockwise around the circle. Note that in the circle in (a) the boundary of the recovered disk isapproximated with σB = 0.001 using B100,12v,resulting in the inscribed disk, while in (b) the boundary is constructed using approximate interpolation using σA = σB = 0.001 and applying B100,12A12,12Iv.
Mentions: We begin by applying the process to the recovery of the boundary of a disk defined parametrically by 12 uniformly distributedpoints with no random errors in the data as shown in Figure 1. The figureclearly illustrates the aforementioned difficulty of attempting to approximate(smooth parametric data).

Bottom Line: Determining the outline or boundary contour of a two-dimensional object, or the surface of a three-dimensional object poses difficulties particularly when there is substantial measurement noise or uncertainty.The technique is applied to parametric boundary data and has potential applications in biomedical imaging.It should be considered as one of several techniques to improve the visualization of images.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, College of Science and Technology, The University of Southern Mississippi, Hattiesburg, MS 39406-0001, USA. joseph.kolibal@usm.edu

ABSTRACT
Determining the outline or boundary contour of a two-dimensional object, or the surface of a three-dimensional object poses difficulties particularly when there is substantial measurement noise or uncertainty. By adapting the mathematical approach of stochastic function recovery to this task, it is possible to obtain usable estimates for these boundaries, even in the presence of large amounts of noise. The technique is applied to parametric boundary data and has potential applications in biomedical imaging. It should be considered as one of several techniques to improve the visualization of images.

Show MeSH
Related in: MedlinePlus