通过自适应交叉最大化实现无漂移的高吞吐量纳米学
Hongqiang Ma1,2, Maomao Chen1, Phuong Nguyen1,2
1Department of Medicine, Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Science advances
|May 23, 2024
概括
我们开发了自适应交叉最大化 (AIM),一种通过精确纠正高频漂移来提高单分子局部化显微镜 (SMLM) 解析度的新方法. 在标准硬件上,AIM有效地提高了SMLM图像质量.
科学领域:
- 生物物理学的生物物理.
- 显微镜的使用方法
- 计算生物学 计算生物学
背景情况:
- 单分子定位显微镜 (SMLM) 对于纳米生物成像至关重要.
- 在SMLM中,低于最佳分辨率的原因往往是未经纠正的样本漂移.
- 现有的漂移校正方法与高频漂移和大数据集作斗争.
研究的目的:
- 开发一种新的,高效的,无模型的算法来纠正SMLM中的漂移.
- 通过精确跟踪高频漂移来提高SMLM的分辨率.
- 为改善SMLM数据质量提供一个用户友好的软件解决方案.
主要方法:
- 适应交叉最大化 (AIM) 算法利用整个数据集信息.
- 强大的漂移跟踪的无模型方法.
- 适用于模拟和实验性高通量SMLM数据集.
主要成果:
- 对于高频漂移,AIM实现了斯特罗姆级的跟踪精度.
- 在各种成像条件下表现出强大而高效的性能.
- 在模拟和生物SMLM数据中显著提高分辨率.
结论:
- AIM有效地将漂移校正错误降到最低,特别是高频漂移.
- 该方法为SMLM系统提供了即时分辨率增强.
- AIM是用于标准CPU的计算效率高,可访问的软件解决方案.
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