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Dynamically-Collimated Digital Tomosynthesis Reconstruction by Using a Compressed-Sensing Based Algorithm

Abstract

Conventional digital tomosynthesis (DTS) reconstruction by using the filtered-backprojection algorithm requires a full field-of-view scan and relatively dense projections to obtain high-quality images, which results in a high radiation dose to patients. Interior DTS (iDTS) with a proper collimator offers a possible imaging modality for reducing the dose of radiation delivered because the X-ray beam is able to target a small region-of-interest (ROI) containing the target area. Collimators for iDTS often have a fixed rectangular shape, but focusing the X-ray beam on an arbitrarily shaped ROI would be preferable because it further reduces the excessive radiation dose. In this study, we propose a new iDTS scan method to create an ROI with an arbitrary shape to minimize the radiation dose at each angle of view. We used a compressed-sensing-based algorithm for accurate iDTS reconstruction. To validate the proposed method, we performed a systematic simulation and an experiment, and we investigated the image characteristics. Our results indicate that the proposed method may effectively reduce radiation dose in iDTS in real imaging systems.

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Acknowledgments

This study was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korea Ministry of Science and ICT (NRF-2017R1A2B2002891).

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Correspondence to Hyosung Cho.

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Park, S., Kim, G., Cho, H. et al. Dynamically-Collimated Digital Tomosynthesis Reconstruction by Using a Compressed-Sensing Based Algorithm. J. Korean Phys. Soc. 76, 66–72 (2020). https://doi.org/10.3938/jkps.76.66

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Keywords

  • Interior digital tomosynthesis
  • Dynamic collimation
  • Compressed-sensing