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EFFICIENT SCANNING FOR EM BASED TARGET LOCALIZATION

机译:基于EM的目标定位的高效扫描

摘要

We presented an approach for speeding-up image acquisition when tasked with localizing specific structures in FIB-SEM imagery. It exploits the fact that low-quality images can be acquired faster than higher-quality ones and yet be sufficient for inference purposes. We have demonstrated greater than five-fold speed-ups at very little loss in accuracy in the context of mitochondria and synapse detection. Furthermore, the algorithm we propose is generic and applicable to many imaging modalities that allow trading quality for speed. The disclosed method of data acquisition for an apparatus having a Scanning Electron Microscope (SEM) for microscopic imaging and a Focused Ion Beam (FIB) unit for sample milling comprises the following steps: scanning a sample with the SEM to obtain an image region (I'); analyzing the image region with a classifier function (hi ) that operates on the image region and returns a classification image whose content depends on whether the classifier estimates that a pixel in the image region belongs to a determined target structure or not; searching in the classification image for disjoint regions that indicate potential target locations and adding the regions so found to a list of candidates; iterating the steps of scanning, analyzing and searching on the members of the list of candidates.
机译:我们提出了一种在FIB-SEM图像中定位特定结构时加快图像获取速度的方法。它利用了以下事实:低质量的图像可以比高质量的图像更快地获取,但足以用于推理。我们已经证明,在线粒体和突触检测的情况下,速度提高了五倍以上,而准确性几乎没有损失。此外,我们提出的算法是通用的,适用于允许以质量换取速度的许多成像模式。具有具有用于显微成像的扫描电子显微镜(SEM)和用于样品研磨的聚焦离子束(FIB)单元的设备的公开数据获取方法包括以下步骤:用SEM扫描样品以获得图像区域(I)。 ');使用对图像区域进行操作的分类器功能(hi)分析图像区域,并返回其内容取决于分类器是否估计图像区域中的像素属于确定的目标结构的分类图像;在分类图像中搜索指示潜在目标位置的不相交区域,并将找到的区域添加到候选列表中;重复扫描,分析和搜索候选列表成员的步骤。

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