TY - GEN

T1 - Density Estimation in X-ray Computed Tomography using the Alvarez-Macovski Model

AU - Yang, Qiheng

AU - Chakraborty, Nirjhor

AU - Lakshtanov, Dmitry

AU - Sheppard, Adrian

AU - Kingston, Andrew

N1 - Publisher Copyright:
© 2021 SPIE. All rights reserved.

PY - 2021

Y1 - 2021

N2 - We introduce a method to extract density information from an x-ray computed tomography (XCT) volume that is more accurate than simply assuming density is proportional to CT number. XCT is a versatile tool for analysis, however, for lab-based XCT machines that employ polychromatic x-rays, it is difficult to extract anything more than the crudest quantitative data from the sample. Reconstructed tomograms values are, in theory, the x-ray attenuation coefficients of the material. However, due to the polychromatic nature of the beam, and effects such as beam hardening, such an interpretation of real data is rarely feasible. The Alvarez-Macovski (AM) equation, which is used in quantitative XCT reconstruction algorithms, provides a model of x-ray attenuation. We use the AM equation to extract quantitative information from conventionally reconstructed tomograms, provided it is not too severely affected by beam-hardening artefacts. In essence, we assume that the tomogram values are proportional to the attenuation coefficients of the AM equation at a mean x-ray energy. Then, given a calibration scan which contains enough materials, we can solve the AM equation for the unknown coefficients and exponents. We then apply it to tomograms of objects with similar shape and material composition. The quantitative data extracted thus provides a more accurate estimate of both per-material density and bulk density.

AB - We introduce a method to extract density information from an x-ray computed tomography (XCT) volume that is more accurate than simply assuming density is proportional to CT number. XCT is a versatile tool for analysis, however, for lab-based XCT machines that employ polychromatic x-rays, it is difficult to extract anything more than the crudest quantitative data from the sample. Reconstructed tomograms values are, in theory, the x-ray attenuation coefficients of the material. However, due to the polychromatic nature of the beam, and effects such as beam hardening, such an interpretation of real data is rarely feasible. The Alvarez-Macovski (AM) equation, which is used in quantitative XCT reconstruction algorithms, provides a model of x-ray attenuation. We use the AM equation to extract quantitative information from conventionally reconstructed tomograms, provided it is not too severely affected by beam-hardening artefacts. In essence, we assume that the tomogram values are proportional to the attenuation coefficients of the AM equation at a mean x-ray energy. Then, given a calibration scan which contains enough materials, we can solve the AM equation for the unknown coefficients and exponents. We then apply it to tomograms of objects with similar shape and material composition. The quantitative data extracted thus provides a more accurate estimate of both per-material density and bulk density.

KW - Computed tomography

KW - Density mapping

KW - Micro-tomography

KW - Quantitative imaging

UR - http://www.scopus.com/inward/record.url?scp=85123055655&partnerID=8YFLogxK

U2 - 10.1117/12.2595473

DO - 10.1117/12.2595473

M3 - Conference contribution

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Developments in X-Ray Tomography XIII

A2 - Muller, Bert

A2 - Wang, Ge

PB - SPIE

T2 - Developments in X-Ray Tomography XIII 2021

Y2 - 1 August 2021 through 5 August 2021

ER -