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Prior frequency guided diffusion model for limited angle (LA)-CBCT reconstruction.

Jiacheng Xie1, Hua-Chieh Shao1, Yunxiang Li1

  • 1The Advanced Imaging and Informatics for Radiation Therapy (AIRT) Laboratory, The Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States of America.

Physics in Medicine and Biology
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Summary
This summary is machine-generated.

This study introduces a novel diffusion model framework, Prior Frequency-Guided Diffusion Model (PFGDM), for reconstructing high-quality limited-angle cone-beam computed tomography (LA-CBCT) images. PFGDM significantly improves image quality and preserves anatomical structures, even with minimal scan data.

Keywords:
cone-beam CTdiffusion modelimage reconstructionlimited angle

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Area of Science:

  • Medical Imaging
  • Radiotherapy Physics
  • Computational Imaging

Background:

  • Cone-beam computed tomography (CBCT) is crucial for image-guided radiotherapy.
  • Limited-angle CBCT (LA-CBCT) reconstruction is challenging due to severe under-sampling artifacts, posing an ill-posed inverse problem.
  • Diffusion models offer potential for image reconstruction by learning data distributions.

Purpose of the Study:

  • To develop a robust and structure-preserving LA-CBCT reconstruction framework using diffusion models.
  • To investigate the efficacy of incorporating prior CT scan information as a conditioning mechanism.
  • To compare the performance of the proposed framework against existing LA-CBCT reconstruction methods.

Main Methods:

  • Developed a Prior Frequency-Guided Diffusion Model (PFGDM) framework for LA-CBCT reconstruction.
  • Utilized a conditioned diffusion model as a regularizer, guided by high-frequency information from patient-specific prior CT scans.
  • Introduced two variants, PFGDM-A and PFGDM-B, with distinct conditioning schemes based on prior CT information application.

Main Results:

  • PFGDM demonstrated superior performance over traditional and other diffusion model-based methods in LA-CBCT reconstruction.
  • PFGDM-A and PFGDM-B achieved significantly higher Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) across various scan angles (120°, 90°, 30°).
  • PFGDM-B showed particularly strong results with mean PSNR/SSIM of 28.20(1.28)/0.954(0.011) at 120° and 23.72(1.19)/0.894(0.034) at 30°, outperforming DiffusionMBIR (19.61(2.47)/0.807(0.048) at 30°).

Conclusions:

  • The PFGDM framework enables high-quality LA-CBCT reconstruction even with very limited gantry angles.
  • This advancement facilitates faster and more flexible CBCT scanning protocols, leading to reduced radiation dose for patients.
  • PFGDM offers a promising solution for improving imaging efficiency and patient safety in image-guided radiotherapy.