EpiCure (Epithelial Curation): a versatile and handy tool for curation of epithelial segmentation
Abstract
Investigating single-cell dynamics and morphology in tissues and embryos requires highly accurate quantitative analysis of microscopy images. Despite significant advances in the field of bioimage analysis, even the most sophisticated segmentation and tracking algorithms inevitably produce errors (e.g. : over segmentation, missing objects, miss-connected objects). Although error rate may be small, their propagation throughout a time-lapse sequence has catastrophic effects on the accuracy of tracking and extraction of single cell parameters. Extracting single cell temporal information in the context of tissue/embryo requires thus expert curation to identify and correct segmentation errors. In the movies commonly used in developmental biology and stem cell research, both the number of imaged cells and the duration of recording are large, making this manual correction task extremely timeconsuming. This has now become a major bottleneck in the fields of development, stem cell biology and bioimage analysis. We present here EpiCure (Epithelial Curation), a versatile tool designed to streamline and accelerate manual curation of segmentation and tracking in 2D movies of large epithelial tissues. EpiCure uses temporal information and morphometric parameters to automatically identify segmentation and tracking errors and provides userfriendly tools to correct them. It focuses on ergonomics and offers several visualization options to help navigating in movies of tissue covering a large number of cells, speeding up the detection of errors and their curation. EpiCure is highly interoperable and supports input from a wide range of segmentation tools. It also includes multiple export filters, enabling seamless integration with downstream analysis pipelines. In this paper, using movies from several animal models, we highlight the importance of curating cell segmentation and tracking for accurate downstream analysis, and demonstrate how EpiCure helps the curation process for extracting accurate single cell dynamics and cellular events detection, making it faster and amenable on large dataset.
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BibTeX
@article{letort2026epicure,
title = {{EpiCure (Epithelial Curation): a versatile and handy tool for curation of epithelial segmentation}},
author = {Gaëlle Letort and Léo Valon and Arthur Michaut and Tom Cumming and Laura Xénard and Minh-Son Phan and Nicolas Dray and Curtis Rueden and François Schweisguth and Jérôme Gros and Laure Bally-Cuif and Jean-Yves Tinevez and Romain Levayer},
journal = {Development},
year = {2026},
month = jul,
doi = {10.1242/dev.205701},
url = {https://pasteur.hal.science/pasteur-05622352v2},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - EpiCure (Epithelial Curation): a versatile and handy tool for curation of epithelial segmentation
AU - Gaëlle Letort
AU - Léo Valon
AU - Arthur Michaut
AU - Tom Cumming
AU - Laura Xénard
AU - Minh-Son Phan
AU - Nicolas Dray
AU - Curtis Rueden
AU - François Schweisguth
AU - Jérôme Gros
AU - Laure Bally-Cuif
AU - Jean-Yves Tinevez
AU - Romain Levayer
PY - 2026
DA - 2026/07/20
JO - Development
DO - 10.1242/dev.205701
UR - https://pasteur.hal.science/pasteur-05622352v2
AB - Investigating single-cell dynamics and morphology in tissues and embryos requires highly accurate quantitative analysis of microscopy images. Despite significant advances in the field of bioimage analysis, even the most sophisticated segmentation and tracking algorithms inevitably produce errors (e.g. : over segmentation, missing objects, miss-connected objects). Although error rate may be small, their propagation throughout a time-lapse sequence has catastrophic effects on the accuracy of tracking and extraction of single cell parameters. Extracting single cell temporal information in the context of tissue/embryo requires thus expert curation to identify and correct segmentation errors. In the movies commonly used in developmental biology and stem cell research, both the number of imaged cells and the duration of recording are large, making this manual correction task extremely timeconsuming. This has now become a major bottleneck in the fields of development, stem cell biology and bioimage analysis. We present here EpiCure (Epithelial Curation), a versatile tool designed to streamline and accelerate manual curation of segmentation and tracking in 2D movies of large epithelial tissues. EpiCure uses temporal information and morphometric parameters to automatically identify segmentation and tracking errors and provides userfriendly tools to correct them. It focuses on ergonomics and offers several visualization options to help navigating in movies of tissue covering a large number of cells, speeding up the detection of errors and their curation. EpiCure is highly interoperable and supports input from a wide range of segmentation tools. It also includes multiple export filters, enabling seamless integration with downstream analysis pipelines. In this paper, using movies from several animal models, we highlight the importance of curating cell segmentation and tracking for accurate downstream analysis, and demonstrate how EpiCure helps the curation process for extracting accurate single cell dynamics and cellular events detection, making it faster and amenable on large dataset.
SN - 0950-1991
SN - 1477-9129
ER -