用高斯核加速3D光声成像重建，实现亚秒级速度
GPAIR: Gaussian-Kernel-Based Ultrafast 3D Photoacoustic Iterative Reconstruction
- 用高斯核替代传统网格，实现连续空间建模
- 840万像素3D图像重建仅需亚秒级时间
- 适合需要实时大尺度成像的临床研究
尽管迭代重建（IR）算法可显著修正光声计算机断层成像（PACT）中的重建伪影，但其计算耗时长，尤其在大规模三维（3D）成像中需数分钟至数小时。本文提出一种超快速3D PACT迭代重建方法——高斯核超快3D光声迭代重建（GPAIR），实现计算速度的数量级提升。GPAIR将传统空间网格替换为连续各向同性高斯核，推导出压力波的解析闭式表达，并通过强大的GPU加速可微Triton算子实现高效计算。在动物实验中，对包含840万体素的3D目标，GPAIR实现亚秒级重建速度。该革命性加速使近实时的大规模3D光声重建成为可能，显著推动3D PACT向临床应用迈进。
原文摘要 · Abstract (English)
Although the iterative reconstruction (IR) algorithm can substantially correct reconstruction artifacts in photoacoustic (PA) computed tomography (PACT), it suffers from long reconstruction times, especially for large-scale three-dimensional (3D) imaging in which IR takes hundreds of seconds to hours. The computing burden severely limits the practical applicability of IR algorithms. In this work, we proposed an ultrafast IR method for 3D PACT, called Gaussian-kernel-based Ultrafast 3D Photoacoustic Iterative Reconstruction (GPAIR), which achieves orders-of-magnitude acceleration in computing. GPAIR transforms traditional spatial grids with continuous isotropic Gaussian kernels. By deriving analytical closed-form expression for pressure waves and implementing powerful GPU-accelerated differentiable Triton operators, GPAIR demonstrates extraordinary ultrafast sub-second reconstruction speed for 3D targets containing 8.4 million voxels in animal experiments. This revolutionary ultrafast image reconstruction enables near-real-time large-scale 3D PA reconstruction, significantly advancing 3D PACT toward clinical applications.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。