arXiv:2506.13545cs.CV2025-06被引 4

用90度扫描重建高质量锥光束CT,大幅缩短时间与降低剂量。

Limited-Angle CBCT Reconstruction via Geometry-Integrated Cycle-domain Denoising Diffusion Probabilistic Models

  • 双域协同:先补全投影数据,再优化图像,融合投影与图像先验。
  • 90度扫描下均方误差35.5 HU,SSIM达0.84,软组织更清晰。
  • 适合放射治疗中时间或剂量受限场景,临床实用性强。

锥光束CT(CBCT)广泛用于放疗影像引导,提升定位精度、自适应计划和运动管理。但旋转慢导致运动伪影、模糊及剂量增加。本文提出一种几何集成的循环域去噪扩散模型(LA-GICD),通过解析正向/反向投影算子连接两个去噪扩散模型(DDPM)。Projection-DDPM补全缺失投影,经反投影后,Image-DDPM优化体积。该双域设计利用投影与图像空间互补先验,实现≤90°有限角扫描下的高质量重建。基于78例规划CT在常见CBCT几何中训练评估,平均绝对误差35.5 HU,SSIM 0.84,PSNR 29.8 dB,伪影显著减少,软组织对比度提升。该方法仅需单次90°扫描,实现无伪影、高对比度重建,使采集时间与剂量降低四倍,兼顾数据保真与解剖合理性,为短弧采集提供可临床应用的解决方案。

原文摘要 · Abstract (English)

Cone-beam CT (CBCT) is widely used in clinical radiotherapy for image-guided treatment, improving setup accuracy, adaptive planning, and motion management. However, slow gantry rotation limits performance by introducing motion artifacts, blurring, and increased dose. This work aims to develop a clinically feasible method for reconstructing high-quality CBCT volumes from consecutive limited-angle acquisitions, addressing imaging challenges in time- or dose-constrained settings. We propose a limited-angle (LA) geometry-integrated cycle-domain (LA-GICD) framework for CBCT reconstruction, comprising two denoising diffusion probabilistic models (DDPMs) connected via analytic cone-beam forward and back projectors. A Projection-DDPM completes missing projections, followed by back-projection, and an Image-DDPM refines the volume. This dual-domain design leverages complementary priors from projection and image spaces to achieve high-quality reconstructions from limited-angle (<= 90 degrees) scans. Performance was evaluated against full-angle reconstruction. Four board-certified medical physicists conducted assessments. A total of 78 planning CTs in common CBCT geometries were used for training and evaluation. The method achieved a mean absolute error of 35.5 HU, SSIM of 0.84, and PSNR of 29.8 dB, with visibly reduced artifacts and improved soft-tissue clarity. LA-GICD's geometry-aware dual-domain learning, embedded in analytic forward/backward operators, enabled artifact-free, high-contrast reconstructions from a single 90-degree scan, reducing acquisition time and dose four-fold. LA-GICD improves limited-angle CBCT reconstruction with strong data fidelity and anatomical realism. It offers a practical solution for short-arc acquisitions, enhancing CBCT use in radiotherapy by providing clinically applicable images with reduced scan time and dose for more accurate, personalized treatments.

CBCT重建扩散模型放射治疗低剂量成像

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