Cellpose: a generalist algorithm for cellular segmentation

Stringer, Carsen; Wang, Yichen; Michaelos, Michalis; Pachitariu, Marius

doi:10.1101/2020.02.02.931238

Cited by 355 publications

(607 citation statements)

References 40 publications

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“…Confocal stacks through PSM and MPZ tissues were acquired with a z-step size of 0.55µm. Cell membranes were segmented using CellPose 43 . The resulting segmented image is overlaid on the confocal section showing both the secreted fluorescent reporter in the extracellular spaces and cell membranes ( Fig.…”

Section: Methodsmentioning

confidence: 99%

Embryonic Tissues as Active Foams

Kim

Pochitaloff

Stooke‐Vaughan

et al. 2020

Preprint

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1The physical state of embryonic tissues emerges from non-equilibrium, collective interactions among constituent cells. Cellular jamming, rigidity transitions and characteristics of glassy dynamics have all been observed in multicellular systems, but there is no unifying framework to describe all these behaviors. Here we develop a general computational framework that enables the description of embryonic tissue dynamics, accounting for the presence of extracellular spaces, complex cell shapes and tension fluctuations. In addition to previously reported rigidity transitions, we find a distinct rigidity transition governed by the magnitude of tension fluctuations. Our results indicate that tissues are maximally rigid at the structural transition between confluent and non-confluent states, with actively-generated tension fluctuations controlling stress relaxation and tissue fluidization. Comparing simulation results to experimental data, we show that tension fluctuations do control rigidity transitions in embryonic tissues, highlighting a key role of non-equilibrium tension dynamics in developmental processes.Many essential processes in multicellular organisms, from organ formation to tissue homeostasis, require a tight control of the tissue physical state 1, 2 . While tissue mechanics and structure at supracellular scales emerge from the collective physical interactions among the constituent cells, their control occurs at cell and subcellular levels. Bridging these scales is essential to understand the physical nature of active (non-equilibrium) multicellular systems and to identify the processes that cells use to control the physical state of embryonic tissues.In vitro experiments of cell monolayers on substrates have revealed characteristics of glassy 2 dynamics 3, 4 and rigidity transitions 5-7 , which are thought to be linked to biological function and multiple pathologies. In contrast, suspended epithelial monolayers are largely solid-like in vitro 8 and show evidence of fracture in vivo 9 . Experiments in embryonic tissues have shown characteristics of glassy dynamics in cell movements 10 , viscous behavior at long-timescales 11 and also structural signatures reminiscent of jamming transitions 12 . Recent in vivo experiments in developing zebrafish embryos showed the existence of a rigidity (fluid-to-solid) transition underlying the formation of the vertebrate body axis, revealing a functional role of rigidity transitions in embryonic development 13 . It is, however, unclear how cells control rigidity transitions in multicellular systems and, more generally, whether all these observed phenomena share a common physical origin.The physical behavior of multicellular systems has been studied theoretically using various approaches. Vertex models [14][15][16][17][18][19] and Cellular Potts models 20, 21 , which account for cell geometry and use equilibrium formulations to describe the physical state of the system, predict a densityindependent rigidity transition in confluent systems that is solely controlled by cell...

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Section: Methodsmentioning

confidence: 99%

Embryonic Tissues as Active Foams

Kim

Pochitaloff

Stooke‐Vaughan

et al. 2020

Preprint

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“…In experiments in which genes were detected without barcodes for projection mapping, we segmented cell bodies using both the DAPI signals and the sequencing signals with Cellpose (Stringer et al, 2020).…”

Section: Barseq2 Data Processingmentioning

confidence: 99%

Integrating barcoded neuroanatomy with spatial transcriptional profiling reveals cadherin correlates of projections shared across the cortex

Sun

Chen

Fischer

et al. 2020

Preprint

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Functional circuits consist of neurons with diverse axonal projections and gene expression. Understanding the molecular signature of projections requires high-throughput interrogation of both gene expression and projections to multiple targets in the same cells at cellular resolution, which is difficult to achieve using current technology. Here, we introduce BARseq2, a technique that simultaneously maps projections and detects multiplexed gene expression by in situ sequencing. We determined the expression of cadherins and cell-type markers in 29,933 cells, and the projections of 3,164 cells in both the mouse motor cortex and auditory cortex. Associating gene expression and projections in 1,349 neurons revealed shared cadherin signatures of homologous projections across the two cortical areas. These cadherins were enriched across multiple branches of the transcriptomic taxonomy. By correlating multi-gene expression and projections to many targets in single neurons with high throughput, BARseq2 provides a path to uncovering the molecular logic underlying neuronal circuits.

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“…It is well recognised that Deep Learning gives very good results, when applied to the nucleus segmentation. There are many published models (both networks topologies, and their software implementations), for example Stardist [11,12] and Cellpose [13]. Typically such highly-optimised statistical methodologies have specific configurations that depend on processor type, graphic card and installed drivers, hence we implement them as plugins.…”

Section: Pluginsmentioning

confidence: 99%

PartSeg, a Tool for Quantitative Feature Extraction From 3D Microscopy Images for Dummies

Bokota

Sroka

Basu

et al. 2020

Preprint

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Background: Bioimaging techniques offer a robust tool for studying molec- ular pathways and morphological phenotypes of cell populations subjected to various conditions. As modern high resolution 3D microscopy provides access to an ever-increasing amount of high quality images, there arises a need for their analysis in an automated, unbiased and simple way. Segmentation of structures within cell nucleus, which is the focus of this paper, presents a new layer of complexity in the form of dense packing and significant signal overlap. At the same time the available segmentation tools provide a steep learning curve for new users with limited technical background. This is especially apparent in bulk processing of image sets, which requires the use of some form of programming notation. Results: In this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of cell nucleus. PartSeg integrates refined versions of several state-of-the-art algorithms, including a new multi-scale approach for segmentation and quantitative analysis of 3D microscopy images. The features and user-friendly interface of PartSeg were carefully planned with biologists in mind, based on analysis of multiple use cases and difficulties encountered with other tools, to offer ergonomic interface with a minimal entry barrier. Bulk processing in an ad-hoc manner is possible without the need for programmer support. As the size of datasets of interest grows, such bulk processing solutions become essential for proper statistical analysis of results. Advanced users can use PartSeg components as a library within Python data processing and visualisation pipelines, for example within Jupyter notebooks. The tool is extensible so that new functionality and algorithms can be added by the use of plugins. For biologists the utility of PartSeg is presented in several scenarios, showing the quantitative analysis of nuclear structures. Conclusions: In this paper, we have presented PartSeg which is a tool for precise and verifiable segmentation and reconstruction of 3D microscopy images. PartSeg is optimised for cell nucleus analysis and offers multi-scale segmentation algorithms best-suited for this task. PartSeg can also be used for bulk processing of multiple images and its components can be reused in other systems or computational experiments. Contact: g.bokota@cent.uw.edu.pl, a.magalska@nencki.edu.pl, d.plewczynski@cent.uw.edu.pl

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Cellpose: a generalist algorithm for cellular segmentation

Cited by 355 publications

References 40 publications

Embryonic Tissues as Active Foams

Embryonic Tissues as Active Foams

Integrating barcoded neuroanatomy with spatial transcriptional profiling reveals cadherin correlates of projections shared across the cortex

PartSeg, a Tool for Quantitative Feature Extraction From 3D Microscopy Images for Dummies

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