On Artifacts in Limited Data Spherical Radon Transform: Flat Observation Surfaces
Linh V. Nguyen

TL;DR
This paper analyzes the artifacts and singularity reconstruction in limited data spherical Radon transform, quantifying how artifacts are smoothed relative to original singularities in 2D and 3D cases.
Contribution
It provides a detailed characterization of artifact strength and singularity reconstruction in limited data spherical Radon transform, extending geometric insights to quantitative smoothing orders.
Findings
Artifacts are smoother than original singularities by k or 2k orders depending on geometry.
Visible singularities are reconstructed with correct order.
Quantifies geometric artifact results from previous studies.
Abstract
In this article, we characterize the strength of the reconstructed singularities and artifacts in a reconstruction formula for limited data spherical Radon transform. Namely, we assume that the data is only available on a closed subset of a hyperplane in (). We consider a reconstruction formula studied in some previous works, under the assumption that the data is only smoothened out to a finite order near the boundary. For the problem in the two dimensional space and is a line segment, the artifacts are generated by rotating a boundary singularity along a circle centered at an end point of . We show that the artifacts are orders smoother than the original singularity. For the problem in the three dimensional space and is a rectangle, we describe that the artifacts are generated by rotating a boundary singularity around…
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Taxonomy
TopicsMedical Imaging Techniques and Applications · Medical Image Segmentation Techniques · Digital Image Processing Techniques
