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Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

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SU-F-BRCD-09: Total Variation (TV) Based Fast Convergent Iterative CBCT Reconstruction with GPU Acceleration.

Q Xu¹, D Yang¹, J Tan¹

¹Washington University in St. Louis, St. Louis, MO.

Medical Physics

|May 19, 2017

Summary

A new iterative algorithm significantly improves Cone Beam CT (CBCT) image quality and reduces radiation dose for therapy. This fast, multi-GPU accelerated method enhances spatial resolution and signal-to-noise ratio compared to standard techniques.

Keywords:

Cone beam computed tomography Dosimetry Image reconstruction Medical image quality Medical image reconstruction Medical image spatial resolution Medical imaging Radiation therapy Spatial resolution Therapeutics

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Area of Science:

Medical Imaging
Computational Imaging
Radiation Oncology

Background:

Cone Beam CT (CBCT) is crucial for radiation therapy, but image quality and radiation dose are significant concerns.
Current reconstruction methods like FDK may not fully address artifacts from limited projection data.

Purpose of the Study:

To develop and validate a fast, iterative image reconstruction algorithm for CBCT.
To enhance image quality and reduce radiation dose in radiation therapy applications.
To achieve near real-time reconstruction using multi-GPU acceleration.

Main Methods:

An iterative algorithm minimizing a weighted least squares cost function with total variation (TV) regularization was implemented.
A multi-GPU implementation was optimized for rapid 3D reconstruction (< 1 minute).
Algorithm performance was assessed using digital (Shepp-Logan) and physical (Catphan-600) phantoms, comparing results to FDK.

Main Results:

The iterative algorithm achieved convergence in as few as 15 iterations for 360-view and 60 iterations for 60-view cases.
Root Mean Square Error (RMSE) was significantly reduced.
Multi-GPU acceleration enabled reconstruction in under 5.4 seconds per iteration.
Iterative reconstructions showed superior spatial resolution and Signal-to-Noise Ratio (SNR) compared to FDK.

Conclusions:

A fast-converging iterative algorithm for CBCT reconstruction was successfully developed.
The algorithm produces higher quality images (spatial resolution, SNR) than commercial FDK methods.
The approach shows potential for significant radiation dose reduction in few-view CBCT scenarios.
This method is expected to benefit image-guided adaptive radiation therapy (IGART) and daily patient localization.