Soft-tissue differentiation and bone densitometry via energy-discriminating X-ray microCT

Viona S.K. Yokhana, Benedicta D. Arhatari, Timur E. Gureyev, Brian Abbey

Research output: Contribution to journalArticleResearchpeer-review

10 Citations (Scopus)

Abstract

X-ray computed tomography (CT) is an important diagnostic tool in medicine as well as being an essential research technique for animal imaging and bioscience. The key aim of this study is to assess the effectiveness, in both simulation and experiment, of differentiating soft tissue from bone as well as bone densitometry, using energy-discriminating X-ray detection. Polychromatic sources, such as standard X-ray tubes, can produce similar CT numbers for materials with different compositions, making differentiation and quantification of tissue and bone extremely challenging. In addition, ‘beam-hardening’ which occurs due to the relative increase in the attenuation of low energy photons compared to high energy photons, can create significant CT artifacts. To improve material contrast and eliminate beam hardening, a number of different approaches have been developed. These include dual-energy CT using two different X-ray tube voltages, photon beam filtration, and post-processing of the data. Here we present an alternative approach using the photon counting PiXirad detector. Simulations are used to establish optimal parameters for data acquisition. This is followed by tomographic experiments performed on a phantom and a mouse embryo. The energy discriminating properties of the detector are exploited to avoid beam-hardening artefacts, to differentiate soft-tissue and bone within the mouse embryo, and to quantify bone density. Compared with polychromatic CT using an integrating detector this approach yields a number of significant advantages for materials specific imaging and quantification.

Original languageEnglish
Pages (from-to)29328-29341
Number of pages14
JournalOptics Express
Volume25
Issue number23
DOIs
Publication statusPublished - 13 Nov 2017
Externally publishedYes

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