Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation.
Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation.
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DOI：
10.1038/s41592-022-01639-4
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发表时间：
2022-11
期刊：
影响因子：
48
通讯作者：
Mougous, Joseph D.
中科院分区：
文献类型：
--
作者：
Cutler, Kevin J.;Stringer, Carsen;Lo, Teresa W.;Rappez, Luca;Stroustrup, Nicholas;Peterson, S. Brook;Wiggins, Paul A.;Mougous, Joseph D.
显微镜技术的进步为在细菌单细胞水平上定量和精确地测量形态和分子现象带来了巨大的希望；然而，这种方法的潜力最终受到独立于其形态或光学特征的忠实分割细胞的方法的可用性的限制。在这里，我们提出了Omnipose，一种深度神经网络图像分割算法。独特的网络输出，如距离场的梯度，使Omnipose能够准确地分割细胞，而当前的算法，包括它的前身Cellpose，会产生错误。我们表明Omnipose在混合细菌培养，抗生素处理的细胞和细长或分支形态的细胞上实现了前所未有的分割性能。此外，Omnipose的好处延伸到非细菌受试者，各种成像方式和三维物体。最后，我们展示了Omnipose在细菌间拮抗过程中出现的极端形态表型表征中的效用。我们的结果区分Omnipose作为一个强大的工具，以表征不同的和任意形状的细胞类型的成像数据。Omnipose是一种用于图像分割的深度神经网络算法，它通过解决从任何模态获得的图像中准确分割形态多样细胞的挑战性问题，改进了现有的方法。
Advances in microscopy hold great promise for allowing quantitative and precise measurement of morphological and molecular phenomena at the single-cell level in bacteria; however, the potential of this approach is ultimately limited by the availability of methods to faithfully segment cells independent of their morphological or optical characteristics. Here, we present Omnipose, a deep neural network image-segmentation algorithm. Unique network outputs such as the gradient of the distance field allow Omnipose to accurately segment cells on which current algorithms, including its predecessor, Cellpose, produce errors. We show that Omnipose achieves unprecedented segmentation performance on mixed bacterial cultures, antibiotic-treated cells and cells of elongated or branched morphology. Furthermore, the benefits of Omnipose extend to non-bacterial subjects, varied imaging modalities and three-dimensional objects. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism. Our results distinguish Omnipose as a powerful tool for characterizing diverse and arbitrarily shaped cell types from imaging data. Omnipose is a deep neural network algorithm for image segmentation that improves upon existing approaches by solving the challenging problem of accurately segmenting morphologically diverse cells from images acquired with any modality.
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影响因子：
3.6
作者：
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通讯作者：
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48
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