Literature DB >> 23318346

A diffusion-based truncated projection artifact reduction method for iterative digital breast tomosynthesis reconstruction.

Yao Lu1, Heang-Ping Chan, Jun Wei, Lubomir M Hadjiiski.   

Abstract

Digital breast tomosynthesis (DBT) has strong promise to improve sensitivity for detecting breast cancer. DBT reconstruction estimates the breast tissue attenuation using projection views (PVs) acquired in a limited angular range. Because of the limited field of view (FOV) of the detector, the PVs may not completely cover the breast in the x-ray source motion direction at large projection angles. The voxels in the imaged volume cannot be updated when they are outside the FOV, thus causing a discontinuity in intensity across the FOV boundaries in the reconstructed slices, which we refer to as the truncated projection artifact (TPA). Most existing TPA reduction methods were developed for the filtered backprojection method in the context of computed tomography. In this study, we developed a new diffusion-based method to reduce TPAs during DBT reconstruction using the simultaneous algebraic reconstruction technique (SART). Our TPA reduction method compensates for the discontinuity in background intensity outside the FOV of the current PV after each PV updating in SART. The difference in voxel values across the FOV boundary is smoothly diffused to the region beyond the FOV of the current PV. Diffusion-based background intensity estimation is performed iteratively to avoid structured artifacts. The method is applicable to TPA in both the forward and backward directions of the PVs and for any number of iterations during reconstruction. The effectiveness of the new method was evaluated by comparing the visual quality of the reconstructed slices and the measured discontinuities across the TPA with and without artifact correction at various iterations. The results demonstrated that the diffusion-based intensity compensation method reduced the TPA while preserving the detailed tissue structures. The visibility of breast lesions obscured by the TPA was improved after artifact reduction.

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Year:  2013        PMID: 23318346      PMCID: PMC4132954          DOI: 10.1088/0031-9155/58/3/569

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  22 in total

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2.  Characterization of masses in digital breast tomosynthesis: comparison of machine learning in projection views and reconstructed slices.

Authors:  Heang-Ping Chan; Yi-Ta Wu; Berkman Sahiner; Jun Wei; Mark A Helvie; Yiheng Zhang; Richard H Moore; Daniel B Kopans; Lubomir Hadjiiski; Ted Way
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Journal:  Eur Radiol       Date:  2005-02-09       Impact factor: 5.315

4.  A comparison of reconstruction algorithms for breast tomosynthesis.

Authors:  Tao Wu; Richard H Moore; Elizabeth A Rafferty; Daniel B Kopans
Journal:  Med Phys       Date:  2004-09       Impact factor: 4.071

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9.  Artifact reduction methods for truncated projections in iterative breast tomosynthesis reconstruction.

Authors:  Yiheng Zhang; Heang-Ping Chan; Berkman Sahiner; Jun Wei; Chuan Zhou; Lubomir M Hadjiiski
Journal:  J Comput Assist Tomogr       Date:  2009 May-Jun       Impact factor: 1.826

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Journal:  Phys Med Biol       Date:  1995-05       Impact factor: 3.609

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  5 in total

1.  [Influence of projection data correction on digital breast tomosynthesis imaging].

Authors:  Xin-Yu Zhang; Hua Zhang; Zhao-Ying Bian; Dong Zeng; Ji He; Xiu-Mei Tian; Jian-Hua Ma; Jing Huang
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2017-03-20

2.  Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction.

Authors:  Yao Lu; Heang-Ping Chan; Jun Wei; Lubomir M Hadjiiski; Ravi K Samala
Journal:  Phys Med Biol       Date:  2017-09-15       Impact factor: 3.609

3.  Segmented separable footprint projector for digital breast tomosynthesis and its application for subpixel reconstruction.

Authors:  Jiabei Zheng; Jeffrey A Fessler; Heang-Ping Chan
Journal:  Med Phys       Date:  2017-03       Impact factor: 4.071

4.  Effect of source blur on digital breast tomosynthesis reconstruction.

Authors:  Jiabei Zheng; Jeffrey A Fessler; Heang-Ping Chan
Journal:  Med Phys       Date:  2019-10-20       Impact factor: 4.071

5.  Detector Blur and Correlated Noise Modeling for Digital Breast Tomosynthesis Reconstruction.

Authors:  Jiabei Zheng; Jeffrey A Fessler; Heang-Ping Chan
Journal:  IEEE Trans Med Imaging       Date:  2017-07-27       Impact factor: 10.048

  5 in total

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