Effect of scatter correction on image noise in contrast-enhanced digital breast tomosynthesis

Hailiang Huang; Xiaoyu Duan; Pranjal Sahu; Wei Zhao

doi:10.1117/12.2561784

22 May 2020 Effect of scatter correction on image noise in contrast-enhanced digital breast tomosynthesis

Hailiang Huang, Xiaoyu Duan, Pranjal Sahu, Wei Zhao

Proceedings Volume 11513, 15th International Workshop on Breast Imaging (IWBI2020); 115130J (2020) https://doi.org/10.1117/12.2561784
Event: Fifteenth International Workshop on Breast Imaging, 2020, Leuven, Belgium

Abstract

The image quality of contrast-enhanced digital breast tomosynthesis (CEDBT) is degraded by scatter radiation. Scatter correction can improve the object contrast and reduce the cupping artifacts, but the image quality is limited by the increased image noise. In this study we investigate the effect of scatter correction on image noise in CEDBT. A scatter correction method based on image convolution with scatter-to-primary ratio kernel was applied. We analyzed the noise power spectrum (NPS) for CEDBT projection images before and after scatter correction using CIRS breast phantoms and evaluated the signal-difference-to-noise ratio (SDNR) of the iodine objects after image reconstruction. We applied image filtering to reduce image noise after scatter correction for phantom and clinical images. A deep learning based denoising technique was applied to further reduce the image noise for clinical images. Our results show that the scatter correction increases the image noise in dual-energy subtracted images, and the improvement in SDNR from scatter correction is limited. Noise reduction applied after scatter removal can regain the benefit in SDNR from scatter correction and further improve the visualization of contrast enhancement in CEDBT.

Citation Download Citation

Hailiang Huang, Xiaoyu Duan, Pranjal Sahu, and Wei Zhao "Effect of scatter correction on image noise in contrast-enhanced digital breast tomosynthesis", Proc. SPIE 11513, 15th International Workshop on Breast Imaging (IWBI2020), 115130J (22 May 2020); https://doi.org/10.1117/12.2561784

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