Metal artifact reduction using a patch-based reconstruction for digital breast tomosynthesis

Lucas R. Borges; Predrag R. Bakic; Andrew D. A. Maidment; Marcelo A. C. Vieira

doi:10.1117/12.2254138

Abstract

Digital breast tomosynthesis (DBT) is rapidly emerging as the main clinical tool for breast cancer screening. Although several reconstruction methods for DBT are described by the literature, one common issue is the interplane artifacts caused by out-of-focus features. For breasts containing highly attenuating features, such as surgical clips and large calcifications, the artifacts are even more apparent and can limit the detection and characterization of lesions by the radiologist. In this work, we propose a novel method of combining backprojected data into tomographic slices using a patch-based approach, commonly used in denoising. Preliminary tests were performed on a geometry phantom and on an anthropomorphic phantom containing metal inserts. The reconstructed images were compared to a commercial reconstruction solution. Qualitative assessment of the reconstructed images provides evidence that the proposed method reduces artifacts while maintaining low noise levels. Objective assessment supports the visual findings. The artifact spread function shows that the proposed method is capable of suppressing artifacts generated by highly attenuating features. The signal difference to noise ratio shows that the noise levels of the proposed and commercial methods are comparable, even though the commercial method applies post-processing filtering steps, which were not implemented on the proposed method. Thus, the proposed method can produce tomosynthesis reconstructions with reduced artifacts and low noise levels.

Conference Presentation

Citation Download Citation

Lucas R. Borges, Predrag R. Bakic, Andrew D. A. Maidment, Marcelo A. C. Vieira, "Metal artifact reduction using a patch-based reconstruction for digital breast tomosynthesis", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 1013221 (9 March 2017); doi: 10.1117/12.2254138; https://doi.org/10.1117/12.2254138

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