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Clinical Efficacy of Novel Image Processing Techniques in the Framework of Filtered Back Projection (FBP) with Digital Breast Tomosynthesis (DBT)

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

Abstract

Digital breast tomosynthesis (DBT) slices are reconstructed from projections acquired within a limited angular range. Out-of-plane artifacts are inevitable in reconstructed DBT images. In this study, we evaluated novel image processing techniques in the framework of filtered backprojection (FBP) and compared the results with reconstruction using a previously used FBP method. The novel FBP reconstruction has an adapted filter kernel, uses unbinned projections, performs an adaptive collapsing scheme and statistical artifact reduction, and applies iterative filtering in the image domain. Fifty-four image pairs were evaluated by three experienced radiologists. The images were compared on a 7-point scale (-3, -2, -1, 0, +1, +2, and +3) according to the following five categories: (1) visibility of noise, (2) diagnostic certainty regarding masses, (3) diagnostic certainty regarding microcalcifications, (4) visibility of structures in the pectoral muscle, and (5) overall image quality. The results showed a statistically significant superiority of the novel FBP reconstruction in comparison with standard FBP (p < 0.05). In particular, the improvement of the diagnostic certainty related to microcalcifications with the novel FBP is noteworthy.

Keywords

  • Tomosynthesis
  • Image Processing
  • DBT
  • FBP

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  • DOI: 10.1007/978-3-319-07887-8_45
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Uchiyama, N. et al. (2014). Clinical Efficacy of Novel Image Processing Techniques in the Framework of Filtered Back Projection (FBP) with Digital Breast Tomosynthesis (DBT). 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_45

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  • DOI: https://doi.org/10.1007/978-3-319-07887-8_45

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07886-1

  • Online ISBN: 978-3-319-07887-8

  • eBook Packages: Computer ScienceComputer Science (R0)