LiveLattice:实时可视化倾斜光片显微镜数据,使用一个内存高效的转换算法
Zichen Wang1,2, Hiroyuki Hakozaki1,2, Gillian McMahon1,2
1Department of Pharmacology, University of California, San Diego, San Diego, CA, 92093.
bioRxiv : the preprint server for biology
|June 10, 2024
概括
一个新的GPU加速算法,WH-Transform,能够快速,内存高效的deskewing和旋转光片显微镜数据. 这允许实时可视化大型4D生物样本,克服计算挑战.
科学领域:
- 生物物理学的生物物理.
- 计算生物学 计算生物学
- 显微镜的使用方法
背景情况:
- 光片光显微镜 (LSFM) 提供了4D成像能力.
- 倾斜样本平面LSFM技术,如iSPIM和LLSM简化样本准备,但需要复杂的后处理.
- 目前对LSFM数据的deskewing和旋转方法是计算密集的,限制了实时分析.
研究的目的:
- 开发一种新的,内存高效的算法,用于快速预处理倾斜样本平面LSFM数据.
- 为了实现实时可视化和分析大型4D显微镜数据集.
- 为了减少LSFM数据处理的计算负担和硬件要求.
主要方法:
- 开发了WH-Transform,这是一个GPU加速的算法,将deskewing和旋转集成到单个转换中.
- 实施了一种存储效率高的方法来处理大型图像堆.
- 与使用大型3D和4D数据集的传统方法相比,基准的WH-Transform.
主要成果:
- 与现有方法相比,WH-Transform至少减少了前处理运行时间的10倍.
- 该算法展示了线性可扩展性,在单个GPU上在不到一分钟的时间内处理15GB的3D堆.
- 对人类肝细胞,肺和大脑器官的4D数据集实现了实时预处理.
结论:
- WH-Transform显著加速LSFM数据预处理,克服了内存和计算限制.
- 该算法可以在标准工作站上实现实时,即时数据处理和可视化.
- 这一进步通过提高LSFM,SPIM和类似显微镜的可用性来彻底改变生物成像应用.
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