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Publication Detail
A Nonlinear Least Squares Method for Solving the Joint Reconstruction and Registration Problem in Digital Breast Tomosynthesis
  • Publication Type:
  • Authors:
    Yang G, Hipwell JH, Hawkes DJ, Arridge SR
  • Publisher:
    Department of Computer Science, Swansea University
  • Publication date:
  • Place of publication:
    Swansea, UK
  • Pagination:
    87, 92
  • Published proceedings:
    Proceedings of Medical Image Understanding and Analysis 2012
  • Editors:
    Xie JXH
  • ISBN-10:
  • Status:
  • Language:
  • Keywords:
    Image reconstruction, Image registration, Digital breast tomosynthesis, Limited angle tomography, Inverse problem, Fully coupled optimisation, Decoupled approach
  • Notes:
    Accepted as Oral Presentation 16th Conference on Medical Image Understanding and Analysis held at Swansea University 09 - 11 Jul 2012
Digital Breast Tomosynthesis (DBT) offers potential insight into the fine details of normal fibroglandular tissues and abnormal lesions, e.g., masses and micro-calcifications associated with breast cancer, by the production of a pseudo-3D image. In addition, it avoids the superposition, which is usually found in X-ray mammography, with a comparable radiation dose. Algorithms to aid the human observer process DBT data sets involve two key tasks: reconstruction and registration. In established medical image modalities these tasks are normally performed sequentially; the images are reconstructed and then registered. In this paper, we hypothesise that, for DBT in particular, combining the optimisation processes of reconstruction and registration into a single algorithm will offer satisfactory for both tasks. Based on this hypothesis, we have devised a mathematical framework to combine these two tasks, and have implemented both affine and non-linear B-spline registration transformation models as plug-ins. By applying our algorithm to various simulated data, we demonstrate the success of our method in terms of both reconstruction fidelity and in the registration accuracy of the recovered transformations.
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