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Centroid calculation of the blastomere from 3D Z-Stack image data of a 2-cell mouse embryo

机译:根据2细胞小鼠胚胎的3D Z-Stack图像数据计算卵裂球的质心

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During cell surgery, cell manipulation tasks such as placement of cells, extraction of organelles, blastomeres, or other structures from within a cell are essential. To enable these tasks, it is necessary to locate the centroid of such objects within a cell, to be able to position micromanipulators to carry out such tasks. Calculation of the centroid of objects within a cell is necessary to enable vision-based feedback control to micromanipulators for automation of cell tasks. In this paper, we propose a methodology to address the calculation of the centroid of blastomeres within a mouse embryo. This is achieved with z-stack image data from 2D cell images. Z-stack images are captured at uniform intervals over the cell depth, by keeping the embryo fixed and moving the focal plane. Individual (2D) images of the z-stack are then processed. Blastomeres in each image are segmented with existing image processing techniques and converted to mask images. From these masked images, the 2D blastomere image centroids are calculated, allowing the centroid of the blastomere volume in 3D to be computed. The proposed calculation of the blastomere centroid is a critical step in determining the centroid of objects within a cell, to facilitate automation of cell surgery tasks. (C) 2019 Elsevier Ltd. All rights reserved.
机译:在细胞外科手术期间,细胞操作任务(如细胞放置,细胞器中细胞器,卵裂球或其他结构的提取)至关重要。为了实现这些任务,有必要在细胞内定位此类对象的质心,以便能够定位微操纵器以执行此类任务。计算单元内对象的质心是必要的,以实现对微型操纵器的基于视觉的反馈控制,从而实现单元任务的自动化。在本文中,我们提出了一种方法来解决小鼠胚胎中卵裂球质心的计算问题。这是通过2D单元图像的z堆栈图像数据实现的。通过保持胚胎固定并移动焦平面,以均匀的间隔在细胞深度上捕获Z堆栈图像。然后处理z堆栈的各个(2D)图像。使用现有的图像处理技术对每个图像中的弹性体进行细分,并将其转换为蒙版图像。根据这些蒙版图像,可以计算2D卵裂球图像质心,从而可以计算3D中卵裂球体积的质心。拟议的卵裂球质心的计算是确定细胞内物体质心的关键步骤,以促进细胞手术任务的自动化。 (C)2019 Elsevier Ltd.保留所有权利。

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