Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor...

Area of Science:

• Medical Imaging
• Computational Imaging
• Radiology

Background:

• Low-dose X-ray cone beam computed tomography (CBCT) is gaining interest in dentistry, radiotherapy, and small animal imaging.
• Widespread clinical adoption of low-dose CBCT is hindered by the need for more evaluation and faster, high-quality reconstruction algorithms.

Purpose of the Study:

• To develop an accelerated and high-quality iterative reconstruction algorithm for low-dose CBCT.
• To improve the speed and image fidelity of CBCT reconstruction.

Main Methods:

• Proposed an iterative reconstruction method accelerating ordered-subsets (OS) reconstruction using a power factor.
• Combined the power-accelerated OS method with total-variation (TV) minimization.
• Evaluated the method using simulations and phantom studies.

Main Results:

• The proposed method significantly accelerates conventional OS methods.
• Demonstrated greatly increased convergence speed in early iterations.
• Applying TV minimization further improved image quality while maintaining fast convergence.

Conclusions:

• The developed iterative reconstruction method offers a viable solution for accelerating low-dose CBCT.
• The combination of power acceleration and TV minimization enhances both speed and image quality, paving the way for wider clinical use.