A Novel Interpretation of the Radon Transform's Ray- and Pixel-Driven Discretizations under Balanced Resolutions

Fuente: arXiv
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Main Author: Huber, Richard
Format: Preprint
Published: 2025
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author Huber, Richard
author_facet Huber, Richard
contents Tomographic investigations are a central tool in medical applications, allowing doctors to image the interior of patients. The corresponding measurement process is commonly modeled by the Radon transform. In practice, the solution of the tomographic problem requires discretization of the Radon transform and its adjoint (called the backprojection). There are various discretization schemes; often structured around three discretization parameters: spatial-, detector-, and angular resolutions. The most widespread approach uses the ray-driven Radon transform and the pixel-driven backprojection in a balanced resolution setting, i.e., the spatial resolution roughly equals the detector resolution. The use of these particular discretization approaches is based on anecdotal reports of their approximation performance, but there is little rigorous analysis of these methods' approximation errors. This paper presents a novel interpretation of ray-driven and pixel-driven methods as convolutional discretizations, illustrating that from an abstract perspective these methods are similar. Moreover, we announce statements concerning the convergence of the ray-driven Radon transform and the pixel-driven backprojection under balanced resolutions. Our considerations are supported by numerical experiments highlighting aspects of the discussed methods.
format Preprint
id arxiv_https___arxiv_org_abs_2501_11451
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Novel Interpretation of the Radon Transform's Ray- and Pixel-Driven Discretizations under Balanced Resolutions
Huber, Richard
Numerical Analysis
Functional Analysis
44A12, 65R10, 94A08
Tomographic investigations are a central tool in medical applications, allowing doctors to image the interior of patients. The corresponding measurement process is commonly modeled by the Radon transform. In practice, the solution of the tomographic problem requires discretization of the Radon transform and its adjoint (called the backprojection). There are various discretization schemes; often structured around three discretization parameters: spatial-, detector-, and angular resolutions. The most widespread approach uses the ray-driven Radon transform and the pixel-driven backprojection in a balanced resolution setting, i.e., the spatial resolution roughly equals the detector resolution. The use of these particular discretization approaches is based on anecdotal reports of their approximation performance, but there is little rigorous analysis of these methods' approximation errors. This paper presents a novel interpretation of ray-driven and pixel-driven methods as convolutional discretizations, illustrating that from an abstract perspective these methods are similar. Moreover, we announce statements concerning the convergence of the ray-driven Radon transform and the pixel-driven backprojection under balanced resolutions. Our considerations are supported by numerical experiments highlighting aspects of the discussed methods.
title A Novel Interpretation of the Radon Transform's Ray- and Pixel-Driven Discretizations under Balanced Resolutions
topic Numerical Analysis
Functional Analysis
44A12, 65R10, 94A08
url https://arxiv.org/abs/2501.11451