Prior Frequency Guided Diffusion Model for Limited Angle (LA)-CBCT Reconstruction

• URL: http://arxiv.org/abs/2404.01448v2
• Date: Tue, 9 Apr 2024 03:47:27 GMT
• Title: Prior Frequency Guided Diffusion Model for Limited Angle (LA)-CBCT Reconstruction
• Authors: Jiacheng Xie, Hua-Chieh Shao, Yunxiang Li, You Zhang,
• Abstract summary: Cone-beam computed tomography (CBCT) is widely used in image-guided radiotherapy. LA-CBCT reconstruction suffers from severe under-sampling artifacts, making it a highly ill-posed inverse problem. We developed a diffusion model-based framework, prior frequency-guided diffusion model (PFGDM) for robust and structure-preserving LA-CBCT reconstruction.
• Score: 2.960150120524893
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cone-beam computed tomography (CBCT) is widely used in image-guided radiotherapy. Reconstructing CBCTs from limited-angle acquisitions (LA-CBCT) is highly desired for improved imaging efficiency, dose reduction, and better mechanical clearance. LA-CBCT reconstruction, however, suffers from severe under-sampling artifacts, making it a highly ill-posed inverse problem. Diffusion models can generate data/images by reversing a data-noising process through learned data distributions; and can be incorporated as a denoiser/regularizer in LA-CBCT reconstruction. In this study, we developed a diffusion model-based framework, prior frequency-guided diffusion model (PFGDM), for robust and structure-preserving LA-CBCT reconstruction. PFGDM uses a conditioned diffusion model as a regularizer for LA-CBCT reconstruction, and the condition is based on high-frequency information extracted from patient-specific prior CT scans which provides a strong anatomical prior for LA-CBCT reconstruction. Specifically, we developed two variants of PFGDM (PFGDM-A and PFGDM-B) with different conditioning schemes. PFGDM-A applies the high-frequency CT information condition until a pre-optimized iteration step, and drops it afterwards to enable both similar and differing CT/CBCT anatomies to be reconstructed. PFGDM-B, on the other hand, continuously applies the prior CT information condition in every reconstruction step, while with a decaying mechanism, to gradually phase out the reconstruction guidance from the prior CT scans. The two variants of PFGDM were tested and compared with current available LA-CBCT reconstruction solutions, via metrics including PSNR and SSIM. PFGDM outperformed all traditional and diffusion model-based methods. PFGDM reconstructs high-quality LA-CBCTs under very-limited gantry angles, allowing faster and more flexible CBCT scans with dose reductions.

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