1 February 2018 Phantom-based study exploring the effects of different scatter correction approaches on the reconstructed images generated by contrast-enhanced stationary digital breast tomosynthesis
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Abstract
Stationary digital breast tomosynthesis (sDBT) is an emerging technology in which the single rotating x-ray tube is replaced by a fixed array of multiple carbon nanotube-enabled sources, providing a higher spatial and temporal resolution. As such, sDBT offers a promising platform for contrast-enhanced (CE) imaging. However, given the minimal enhancement above background with standard operational tube settings and iodine dosing, CE breast imaging requires additional acquisition steps to isolate the iodine signal, using either temporal or dual energy subtraction (TS or DES) protocols. Also, correcting for factors that limit contrast is critical, and scatter and noise pose unique challenges during tomosynthesis. This phantom-based study of CE sDBT compared different postacquisition scatter correction approaches on the quality of the reconstructed image slices. Beam-pass collimation was used to sample scatter indirectly, from which an interpolated scatter map was obtained for each projection image. Scatter-corrected projections provided the information for reconstruction. Comparison between the application of different scatter maps demonstrated the significant effect that processing has on the contrast-to-noise ratio and feature detectability (d′) in the final displayed images and emphasized the critical importance of scatter correction during DES.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Connor Puett, Connor Puett, Christina R. Inscoe, Christina R. Inscoe, Yueh Ray Z. Lee, Yueh Ray Z. Lee, Otto Zhou, Otto Zhou, Jianping Lu, Jianping Lu, } "Phantom-based study exploring the effects of different scatter correction approaches on the reconstructed images generated by contrast-enhanced stationary digital breast tomosynthesis," Journal of Medical Imaging 5(1), 013502 (1 February 2018). https://doi.org/10.1117/1.JMI.5.1.013502 . Submission: Received: 25 September 2017; Accepted: 4 January 2018
Received: 25 September 2017; Accepted: 4 January 2018; Published: 1 February 2018
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