利用微图案图像进行深度学习,量化早期分化的人类诱导多能干细胞的空间图案和形成过程。

IF 1.5 4区 工程技术 Q3 MICROSCOPY Journal of microscopy Pub Date : 2024-07-12 DOI:10.1111/jmi.13346
Slo-Li Chu, Kuniya Abe, Hideo Yokota, Dooseon Cho, Yohei Hayashi, Ming-Dar Tsai
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引用次数: 0

摘要

微图案化是量化人类诱导多能干细胞(hiPSCs)多能性的可靠方法,这些细胞分化后会在微图案上形成排序、有序和不重叠的三个胚层空间图案。在本研究中,我们提出了一种深度学习方法,利用微图案图像量化 hiPSC 早期分化阶段胚芽层的空间图案。我们提出了解码和编码 U-net 结构的方法,通过学习标记了 Hoechst(DNA 染色)的 hiPSC 区域与相应的 Hoechst 和明视野微图案图像,来分割 Hoechst 或明视野图像上的 hiPSC。我们还提出了一种 U 型网络结构,用于提取微图案上的胚外区域,以及一种比较各胚层细胞染色荧光图像强度并提取其区域的算法。因此,所提出的方法可以量化具有空间图案的 hiPSC 株系的多能性,包括微图案上胚层和胚外细胞的数量、面积和分布,并通过分割活细胞明视野图像揭示分化早期 hiPSC 和胚层的形成过程。在我们的实验中,分割 Hoechst 和明视野微图案图像的细胞数准确率分别达到 86% 和 85%,细胞区域准确率分别达到 89% 和 81%。对多个 hiPSC 品系、微图案大小、标记群、活细胞和固定细胞的微图案图像的应用表明,在向科学界提供新的 hiPSC 品系之前,所提出的方法有望成为量化该品系多能性的有用方案和工具。
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Deep learning for quantifying spatial patterning and formation process of early differentiated human-induced pluripotent stem cells with micropattern images

Micropatterning is reliable method for quantifying pluripotency of human-induced pluripotent stem cells (hiPSCs) that differentiate to form a spatial pattern of sorted, ordered and nonoverlapped three germ layers on the micropattern. In this study, we propose a deep learning method to quantify spatial patterning of the germ layers in the early differentiation stage of hiPSCs using micropattern images. We propose decoding and encoding U-net structures learning labelled Hoechst (DNA-stained) hiPSC regions with corresponding Hoechst and bright-field micropattern images to segment hiPSCs on Hoechst or bright-field images. We also propose a U-net structure to extract extraembryonic regions on a micropattern, and an algorithm to compares intensities of the fluorescence images staining respective germ-layer cells and extract their regions. The proposed method thus can quantify the pluripotency of a hiPSC line with spatial patterning including cell numbers, areas and distributions of germ-layer and extraembryonic cells on a micropattern, and reveal the formation process of hiPSCs and germ layers in the early differentiation stage by segmenting live-cell bright-field images. In our assay, the cell-number accuracy achieved 86% and 85%, and the cell region accuracy 89% and 81% for segmenting Hoechst and bright-field micropattern images, respectively. Applications to micropattern images of multiple hiPSC lines, micropattern sizes, groups of markers, living and fixed cells show the proposed method can be expected to be a useful protocol and tool to quantify pluripotency of a new hiPSC line before providing it to the scientific community.

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来源期刊
Journal of microscopy
Journal of microscopy 工程技术-显微镜技术
CiteScore
4.30
自引率
5.00%
发文量
83
审稿时长
1 months
期刊介绍: The Journal of Microscopy is the oldest journal dedicated to the science of microscopy and the only peer-reviewed publication of the Royal Microscopical Society. It publishes papers that report on the very latest developments in microscopy such as advances in microscopy techniques or novel areas of application. The Journal does not seek to publish routine applications of microscopy or specimen preparation even though the submission may otherwise have a high scientific merit. The scope covers research in the physical and biological sciences and covers imaging methods using light, electrons, X-rays and other radiations as well as atomic force and near field techniques. Interdisciplinary research is welcome. Papers pertaining to microscopy are also welcomed on optical theory, spectroscopy, novel specimen preparation and manipulation methods and image recording, processing and analysis including dynamic analysis of living specimens. Publication types include full papers, hot topic fast tracked communications and review articles. Authors considering submitting a review article should contact the editorial office first.
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Towards affordable biomedical imaging: Recent advances in low-cost, high-resolution optoacoustic microscopy. TOC - Issue Information A comparison of super-resolution microscopy techniques for imaging tightly packed microcolonies of an obligate intracellular bacterium. Mechanical properties of bone cells studied by atomic force microscopy. Multicamera simultaneous total internal reflection and interference reflection microscopy.
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