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Optimizing High Resolution Reconstruction in Digital Breast Tomosynthesis Using Filtered Back Projection

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Breast Imaging (IWDM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8539))

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Abstract

In Digital Breast Tomosynthesis, a 3D representation of the breast is reconstructed from low-dose projection images acquired over a limited angular range. Each such image contains high level of noise which is often counteracted by a projection binning to yield the CNR desired in clinical applications. However, this approach reduces spatial resolution and makes imaging of high frequency structures such as micro-calcifications challenging. In this paper, we describe a Filtered Back Projection (FBP) reconstruction method optimized to yield improved CNR without sacrificing spatial resolution. The results from our quantitative evaluation and clinical reading by experienced radiologists indicate that the proposed methods can significantly improve contrast and sharpness of micro-calcifications and reduce noise compared to a baseline FBP method with standard filter settings.

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References

  1. Mertelmeier, T., Orman, J., Haerer, W., Dudam, M.K.: Optimizing filtered backprojection reconstruction for a breast tomosynthesis prototype device. In: Proc. SPIE 6142, 61420F-61420F-12 (2006)

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  3. Uchiyama, N., Machida, M., Tani, H., Kikuchi, M., Arai, Y., Otsuka, K., Fieselmann, A., Jerebko, A., Mertelmeier, T.: Clinical Efficacy of Novel Image Processing Techniques in the Framework of Filtered Back Projection (FBP) with Digital Breast Tomosynthesis (DBT). To be appeared in Breast Imaging. LNCS. Springer, Heidelberg (2014)

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© 2014 Springer International Publishing Switzerland

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Abdurahman, S., Dennerlein, F., Jerebko, A., Fieselmann, A., Mertelmeier, T. (2014). Optimizing High Resolution Reconstruction in Digital Breast Tomosynthesis Using Filtered Back Projection. In: Fujita, H., Hara, T., Muramatsu, C. (eds) Breast Imaging. IWDM 2014. Lecture Notes in Computer Science, vol 8539. Springer, Cham. https://doi.org/10.1007/978-3-319-07887-8_73

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  • DOI: https://doi.org/10.1007/978-3-319-07887-8_73

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07886-1

  • Online ISBN: 978-3-319-07887-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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