Topology-based segmentation of 3D confocal images of emerging hematopoietic stem cells in the zebrafish embryo.

Biological imaging Pub Date : 2024-11-11 eCollection Date: 2024-01-01 DOI:10.1017/S2633903X24000102
G Nardi, L Torcq, A A Schmidt, J-C Olivo-Marin
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Abstract

We develop a novel method for image segmentation of 3D confocal microscopy images of emerging hematopoietic stem cells. The method is based on the theory of persistent homology and uses an optimal threshold to select the most persistent cycles in the persistence diagram. This enables the segmentation of the image's most contrasted and representative shapes. Coupling this segmentation method with a meshing algorithm, we define a pipeline for 3D reconstruction of confocal volumes. Compared to related methods, this approach improves shape segmentation, is more ergonomic to automatize, and has fewer parameters. We apply it to the segmentation of membranes, at subcellular resolution, of cells involved in the endothelial-to-hematopoietic transition (EHT) in the zebrafish embryos.

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基于拓扑的斑马鱼胚胎新生造血干细胞三维共聚焦图像分割。
我们开发了一种新的方法,用于图像分割的三维共聚焦显微镜图像的新兴造血干细胞。该方法基于持久同源性理论,使用最优阈值选择持久性图中最持久的循环。这样就可以分割出图像中对比度最高和最具代表性的形状。将此分割方法与网格划分算法相结合,定义了用于共聚焦体三维重建的管道。与相关方法相比,该方法改进了形状分割,更符合人体工程学,自动化程度更高,参数更少。我们将其应用于斑马鱼胚胎中参与内皮到造血转化(EHT)的细胞的亚细胞分辨率的膜分割。
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