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Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image

Qiaofeng Xu1, Deshan Yang2, Jun Tan3

  • 1Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130.

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Accelerated Fast Iterative Shrinkage Thresholding Algorithms (FISTA) significantly reduce cone-beam computed tomography (CBCT) reconstruction times. These new algorithms achieve high image quality for image-guided radiation therapy (IGRT) in under four minutes.

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Area of Science:

  • Medical Imaging
  • Computational Imaging
  • Radiation Oncology

Background:

  • Iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) are crucial for applications like image-guided radiation therapy (IGRT).
  • Existing 3D iterative algorithms, especially those using nonsmooth regularizers, are computationally intensive and impractical for time-sensitive IGRT procedures.

Purpose of the Study:

  • To develop and investigate two variants of the Fast Iterative Shrinkage Thresholding Algorithm (FISTA) for accelerating iterative image reconstruction in CBCT.
  • To address the computational burden of existing algorithms, enabling their use in time-constrained clinical settings like IGRT.

Main Methods:

  • Developed accelerated FISTA variants by replacing the standard gradient-descent step with a subproblem solved using the Ordered Subset Simultaneous Algebraic Reconstruction Technique (OS-SART).
  • Introduced two novel weighted proximal problems and corresponding fast gradient projection algorithms, leveraging the OS-SART preconditioning matrix.
  • Implemented efficient numerical solutions utilizing the parallel processing capabilities of multiple Graphics Processing Units (GPUs).

Main Results:

  • Demonstrated significantly improved convergence rates for the accelerated FISTAs compared to standard FISTAs in both simulation and clinical data studies.
  • Achieved an order-of-magnitude reduction in the number of iterations required to reach a specified reconstruction error.
  • Successfully reconstructed volumetric images from clinical IGRT data in under 4 minutes.

Conclusions:

  • The proposed accelerated FISTA algorithms offer substantial reductions in CBCT image reconstruction time while maintaining image quality.
  • These algorithms, particularly with mixed sparsity-regularization, show potential for enhanced preservation of soft-tissue structures.
  • The systematic evaluation using simulated and clinical datasets confirms the efficacy and potential clinical utility of the developed methods for IGRT.