paper_authors: Ruipeng Guo, Qianwan Yang, Andrew S. Chang, Guorong Hu, Joseph Greene, Christopher V. Gabel, Sixian You, Lei Tian
for: This paper aims to develop a new imaging technique for visualizing complex and dynamic biological processes with high speed and large 3D space-bandwidth product (SBP).
methods: The proposed technique, called EventLFM, combines an event camera with Fourier light field microscopy (LFM) to achieve single-shot 3D wide-field imaging with asynchronous readout and high data throughput.
results: The authors demonstrate the ability of EventLFM to image fast-moving and rapidly blinking 3D samples at KHz frame rates and track GFP-labeled neurons in freely moving C. elegans with high accuracy.Here’s the Chinese translation of the three points:
methods: 该提案的技术是将事件相机与富ouriet light field microscopy（LFM）相结合，实现单次广角成像，并且使用异步读取，以提高数据传输速率。
results: 作者们证明了事件LFM可以在KHz帧率下成像高速和快速闪烁的3D样品，并且可以准确地跟踪在自由移动C. elegans中的GFP标记neuron。Abstract
Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes. Conventional scanning-based techniques necessitate an inherent tradeoff between the acquisition speed and space-bandwidth product (SBP). While single-shot 3D wide-field techniques have emerged as an attractive solution, they are still bottlenecked by the synchronous readout constraints of conventional CMOS architectures, thereby limiting the data throughput by frame rate to maintain a high SBP. Here, we present EventLFM, a straightforward and cost-effective system that circumnavigates these challenges by integrating an event camera with Fourier light field microscopy (LFM), a single-shot 3D wide-field imaging technique. The event camera operates on a novel asynchronous readout architecture, thereby bypassing the frame rate limitations intrinsic to conventional CMOS systems. We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements from EventLFM. We experimentally demonstrate that EventLFM can robustly image fast-moving and rapidly blinking 3D samples at KHz frame rates and furthermore, showcase EventLFM's ability to achieve 3D tracking of GFP-labeled neurons in freely moving C. elegans. We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.
摘要
超速3D成像是生物过程视化中不可或缺的。传统的扫描方式存在固有的质量比速度产品（SBP）交换限制，而单发3D广阔技术受到传统CMOS架构的同步读取限制，因此对数据传输率做出了限制，即保持高SBP的情况下，帧率限制。在这里，我们介绍了EventLFM，一种简单且cost-effective的系统，通过将事件摄像头与快速光场镜微scopio（LFM）结合，绕过了传统CMOS系统中的帧率限制。事件摄像头使用了新的异步读取架构，因此可以快速响应快速变化的3D动态过程。我们还开发了一种简单可靠的事件驱动LFM重构算法，可以可靠地从EventLFM中获取3D动力学。我们实验表明，EventLFM可以Robustly图像高速运动和快速灯泡3D样本，并且可以实现C. elegans中GFP标记的 neuron 3D跟踪。我们认为EventLFM的总体快速速度和大3DSBP可能会开拓新的生物医学应用领域。
Spatiotemporal Image Reconstruction to Enable High-Frame Rate Dynamic Photoacoustic Tomography with Rotating-Gantry Volumetric Imagers
paper_authors: Refik M. Cam, Chao Wang, Weylan Thompson, Sergey A. Ermilov, Mark A. Anastasio, Umberto Villa
For: 这种研究旨在开发一种能够应用于现有的扫描仪器上的快速扫描 PACT 图像重建方法，以解决现有系统中数据缺失的问题，并提高图像重建的精度和速度。* Methods: 该方法基于低级别矩阵估计（LRME），利用空间时间重复性来准确重建4D 空间时间图像。* Results: 数值研究表明，该方法可以准确地重建4D 动态图像，而实验研究则证明了该方法在实际应用中的可靠性和效果。Abstract
Significance: Dynamic photoacoustic computed tomography (PACT) is a valuable technique for monitoring physiological processes. However, current dynamic PACT techniques are often limited to 2D spatial imaging. While volumetric PACT imagers are commercially available, these systems typically employ a rotating gantry in which the tomographic data are sequentially acquired. Because the object varies during the data-acquisition process, the sequential data-acquisition poses challenges to image reconstruction associated with data incompleteness. The proposed method is highly significant in that it will address these challenges and enable volumetric dynamic PACT imaging with existing imagers. Aim: The aim of this study is to develop a spatiotemporal image reconstruction (STIR) method for dynamic PACT that can be applied to commercially available volumetric PACT imagers that employ a sequential scanning strategy. The proposed method aims to overcome the challenges caused by the limited number of tomographic measurements acquired per frame. Approach: A low-rank matrix estimation-based STIR method (LRME-STIR) is proposed to enable dynamic volumetric PACT. The LRME-STIR method leverages the spatiotemporal redundancies to accurately reconstruct a 4D spatiotemporal image. Results: The numerical studies substantiate the LRME-STIR method's efficacy in reconstructing 4D dynamic images from measurements acquired with a rotating gantry. The experimental study demonstrates the method's ability to faithfully recover the flow of a contrast agent at a frame rate of 0.1 s even when only a single tomographic measurement per frame is available. Conclusions: The LRME-STIR method offers a promising solution to the challenges faced by enabling 4D dynamic imaging using commercially available volumetric imagers. By enabling accurate 4D reconstruction, this method has the potential to advance preclinical research.
摘要
significación: La tomografía por sonido fotográfico dinámico (PACT) es una técnica valiosa para monitorear procesos fisiológicos. Sin embargo, las técnicas de PACT dinámicas actuales suelen limitarse a la imagen espacial bidimensional. Los escáneres de PACT volumétricos comerciales suelen emplear una gánglia rotatoria en la que los datos tomográficos se adquieren secuencialmente. Como el objeto varía durante el proceso de adquisición de datos, la adquisición de datos secuenciales plantea desafíos en la reconstrucción de imágenes asociada con la incompletitud de los datos. El método propuesto es altamente significativo ya que abordará estos desafíos y permitirá la imagen de volumetría dinámica PACT con imagers existentes. objetivo: El objetivo de este estudio es desarrollar un método de reconstrucción de imágenes espacio-temporal (STIR) para la PACT dinámica que pueda aplicarse a los imagers volumétricos PACT comerciales que utilizan una estrategia de escaneo secuencial. El método propuesto busca superar los desafíos causados por el número limitado de medidas tomográficas adquiridas por frame. enfoque: Se propone un método de estimación de matrices de baja riqueza (LRME-STIR) para la reconstrucción de imágenes espacio-temporales. El método de LRME-STIR aprovecha las redundancias espacio-temporales para reconstruir precisamente una imagen espacio-temporal de 4D. resultados: Los estudios numéricos respaldan la eficacia del método LRME-STIR en la reconstrucción de imágenes dinámicas de 4D a partir de medidas adquiridas con una gánglia rotatoria. El estudio experimental demuestra la capacidad del método para recuperar fielmente el flujo de un agente de contraste a una tasa de cuadros de 0,1 s, incluso cuando solo se adquieren medidas tomográficas por frame. conclusiones: El método LRME-STIR ofrece una solución prometedora para los desafíos que enfrenta la imagen de volumetría dinámica con imagers existentes. Al permitir la reconstrucción precisa de imágenes de 4D, este método tiene el potencial de avanzar en la investigación preclínica.