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语境高通量3D体积电子显微镜数据采集使用人工智能

Tereza Hurník Konečná¹, Radek Jančík¹, Daniela Slamková¹

¹Materials and Structural Analysis Division, Thermo Fisher Scientific, Vlastimila Pecha 1282/12, Brno 62700, Czech Republic.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada

|March 13, 2026

概括

适应扫描使用人工智能来创建面具,使得3D体积电子显微镜 (vEM) 的高分辨率成像成为可能. 这种动态解析方法显著减少了各种样本中大型数据集的采集时间.

科学领域:

电子显微镜电子显微镜
人工智能的人工智能
生物成像是一种生物成像.

背景情况:

产生大型3D体积电子显微镜 (vEM) 数据集是耗时的.
广泛的生物结构的高分辨率成像存在重大挑战.

研究的目的:

开发一种人工智能驱动的方法来加速3D vEM数据采集.
引入动态分辨率扫描策略,以实现高效的VEM成像.

主要方法:

实现人工智能 (AI) 算法以生成兴趣区域面罩.
开发了一种适应扫描技术,用于动态分辨率数据捕获.
在各种生物样本中应用该方法,包括大脑,寄生虫,细胞和植物.

主要成果:

适应扫描显著减少了数据采集时间.
该方法实现了目标结构的高分辨率成像,同时以较低分辨率捕捉周围区域.
证明了样品不可知论,证明了与各种生物和组织的兼容性.

结论:

多分辨率扫描策略可以提高3D vEM.
这种方法可以节省多达两倍或更多的时间.
允许更高效,更具成本效益地生成更大的vEM数据集,以增加统计能力.

关键词:

3D电子显微镜 3D电子显微镜在FIB-SEM中.人工智能的人工智能是人工智能.深度学习是一种深度学习.音量音量音量音量

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