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@article{2220797,
author = {Hradecká, Lucia and Wiesner, David and Sumbal, Jakub and Sumbalová Koledová, Zuzana and Maška, Martin},
article_number = {1},
doi = {http://dx.doi.org/10.1109/TMI.2022.3210714},
keywords = {organoid segmentation; organoid tracking; brightfield microscopy; deep learning; image synthesis},
language = {eng},
issn = {0278-0062},
journal = {IEEE Transactions on Medical Imaging},
title = {Segmentation and Tracking of Mammary Epithelial Organoids in Brightfield Microscopy},
url = {https://doi.org/10.1109/TMI.2022.3210714},
volume = {42},
year = {2023}
}
TY - JOUR
ID - 2220797
AU - Hradecká, Lucia - Wiesner, David - Sumbal, Jakub - Sumbalová Koledová, Zuzana - Maška, Martin
PY - 2023
TI - Segmentation and Tracking of Mammary Epithelial Organoids in Brightfield Microscopy
JF - IEEE Transactions on Medical Imaging
VL - 42
IS - 1
SP - 281-290
EP - 281-290
SN - 02780062
KW - organoid segmentation
KW - organoid tracking
KW - brightfield microscopy
KW - deep learning
KW - image synthesis
UR - https://doi.org/10.1109/TMI.2022.3210714
N2 - We present an automated and deep-learningbased workflow to quantitatively analyze the spatiotemporal development of mammary epithelial organoids in twodimensional time-lapse (2D+t) sequences acquired using a brightfield microscope at high resolution. It involves a convolutional neural network (U-Net), purposely trained using computer-generated bioimage data created by a conditional generative adversarial network (pix2pixHD), to infer semantic segmentation, adaptive morphological filtering to identify organoid instances, and a shape-similarity-constrained, instance-segmentation-correcting tracking procedure to reliably cherry-pick the organoid instances of interest in time. By validating it using real 2D+t sequences of mouse mammary epithelial organoids of morphologically different phenotypes, we clearly demonstrate that the workflow achieves reliable segmentation and tracking performance, providing a reproducible and laborless alternative to manual analyses of the acquired bioimage data.
ER -
HRADECKÁ, Lucia, David WIESNER, Jakub SUMBAL, Zuzana SUMBALOVÁ KOLEDOVÁ and Martin MAŠKA. Segmentation and Tracking of Mammary Epithelial Organoids in Brightfield Microscopy. \textit{IEEE Transactions on Medical Imaging}. 2023, vol.~42, No~1, p.~281-290. ISSN~0278-0062. Available from: https://dx.doi.org/10.1109/TMI.2022.3210714.
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