提出自监督方法，35倍提速实现声速恢复与超分辨率成像
Coordinate-based Speed of Sound Recovery for Aberration-Corrected Photoacoustic Computed Tomography
- 用像素网格或神经场参数化声速，通过可微成像模型反向传播优化
- 仿真与活体数据验证：声速畸变校正更准，重建速度提升35倍
- 适合需要快速高质光声成像的临床研究者，代码开源
光声计算机断层成像（PACT）是一种无创医学成像技术，类似超声波，应用广泛。传统PACT图像因组织中声速（SOS）分布不均导致波前畸变而质量下降。考虑这些效应可提升图像质量并提供有用医学信息，但直接测量SOS成本高，现有联合重建方法计算量大。传统监督学习在此数据稀缺领域不可行。本文提出一种高效自监督联合重建方法，用于环形阵列PACT系统，同时恢复声速和高质量图像。针对这一半盲逆问题，我们采用像素网格或神经场（NF）参数化声速，并通过可微成像前向模型反向传播梯度直接更新。该方法在仿真中定量验证成功，在实验采集和活体数据上也实现定性成功，比当前最先进方法快35倍。代码与合成数值体模已公开于项目页面：https://lukeli0425.github.io/Coord-SoS-PACT/
原文摘要 · Abstract (English)
Photoacoustic computed tomography (PACT) is a non-invasive imaging modality, similar to ultrasound, with wide-ranging medical applications. Conventional PACT images are degraded by wavefront distortion caused by the heterogeneous speed of sound (SOS) in tissue. Accounting for these effects can improve image quality and provide medically useful information, but measuring the SOS directly is burdensome and the existing joint reconstruction method is computationally expensive. Traditional supervised learning techniques are currently inaccessible in this data-starved domain. In this work, we introduce an efficient, self-supervised joint reconstruction method that recovers SOS and high-quality images for ring array PACT systems. To solve this semi-blind inverse problem, we parametrize the SOS using either a pixel grid or a neural field (NF) and update it directly by backpropagating the gradients through a differentiable imaging forward model. Our method removes SOS aberrations more accurately and 35x faster than the current SOTA. We demonstrate the success of our method quantitatively in simulation and qualitatively on experimentally-collected and in vivo data. Our code and synthetic numerical phantoms are available on our project page: https://lukeli0425.github.io/Coord-SoS-PACT/.
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