Wang Zichen, Hakozaki Hiroyuki, McMahon Gillian, Medina-Carbonero Marta, Schöneberg Johannes
Department of Pharmacology, University of California, San Diego, California, USA.
Department of Chemistry and Biochemistry, University of California, San Diego, California, USA.
J Microsc. 2025 Feb;297(2):123-134. doi: 10.1111/jmi.13358. Epub 2024 Oct 3.
Light-sheet fluorescence microscopy (LSFM), a prominent fluorescence microscopy technique, offers enhanced temporal resolution for imaging biological samples in four dimensions (4D; x, y, z, time). Some of the most recent implementations, including inverted selective plane illumination microscopy (iSPIM) and lattice light-sheet microscopy (LLSM), move the sample substrate at an oblique angle relative to the detection objective's optical axis. Data from such tilted-sample-scan LSFMs require subsequent deskewing and rotation for proper visualisation and analysis. Such data preprocessing operations currently demand substantial memory allocation and pose significant computational challenges for large 4D dataset. The consequence is prolonged data preprocessing time compared to data acquisition time, which limits the ability for live-viewing the data as it is being captured by the microscope. To enable the fast preprocessing of large light-sheet microscopy datasets without significant hardware demand, we have developed WH-Transform, a memory-efficient transformation algorithm for deskewing and rotating the raw dataset, significantly reducing memory usage and the run time by more than 10-fold for large image stacks. Benchmarked against the conventional method and existing software, our approach demonstrates linear runtime compared to the cubic and quadratic runtime of the other approaches. Preprocessing a raw 3D volume of 2 GB (512 × 1536 × 600 pixels) can be accomplished in 3 s using a GPU with 24 GB of memory on a single workstation. Applied to 4D LLSM datasets of human hepatocytes, lung organoid tissue and brain organoid tissue, our method provided rapid and accurate preprocessing within seconds. Importantly, such preprocessing speeds now allow visualisation of the raw microscope data stream in real time, significantly improving the usability of LLSM in biology. In summary, this advancement holds transformative potential for light-sheet microscopy, enabling real-time, on-the-fly data preprocessing, visualisation, and analysis on standard workstations, thereby revolutionising biological imaging applications for LLSM and similar microscopes.
光片荧光显微镜（LSFM）是一种卓越的荧光显微镜技术，可提高对生物样本进行四维（4D；x、y、z、时间）成像的时间分辨率。包括倒置选择性平面照明显微镜（iSPIM）和晶格光片显微镜（LLSM）在内的一些最新技术，使样本基板相对于检测物镜的光轴以倾斜角度移动。来自这种倾斜样本扫描LSFM的数据需要进行后续的去倾斜和旋转，以便进行正确的可视化和分析。目前，此类数据预处理操作需要大量内存分配，并且对于大型4D数据集而言，会带来巨大的计算挑战。其结果是，与数据采集时间相比，数据预处理时间延长，这限制了在显微镜采集数据时实时查看数据的能力。为了在无需大量硬件需求的情况下实现对大型光片显微镜数据集的快速预处理，我们开发了WH变换，这是一种内存高效的变换算法，用于对原始数据集进行去倾斜和旋转，对于大型图像堆栈，可显著减少内存使用并将运行时间缩短10倍以上。与传统方法和现有软件相比，我们的方法展示出线性运行时间，而其他方法的运行时间为立方和二次方。在单个工作站上，使用具有24GB内存的GPU，可在3秒内完成对2GB（512×1536×600像素）的原始3D体积的预处理。将我们的方法应用于人类肝细胞、肺类器官组织和脑类器官组织的4D LLSM数据集，可在数秒内提供快速且准确的预处理。重要的是，这样的预处理速度现在允许实时可视化原始显微镜数据流，显著提高了LLSM在生物学中的可用性。总之，这一进展对光片显微镜具有变革性潜力，能够在标准工作站上进行实时、即时的数据预处理、可视化和分析，从而彻底改变LLSM及类似显微镜的生物成像应用。
