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MARS-Net: Deep learning-based segmentation pipeline for profiling cellular morphodynamics from multiple types of live cell microscopy

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Outgoing claims: the papers this work cites, builds on, or argues with.

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/cyto.a.23701openalex-snapshot
Deep Learning in Image Cytometry: A Review
inferred← citeshttps://doi.org/10.1007/s12257-024-00130-5openalex-snapshot
Automatic cancer nuclei segmentation on histological images: comparison study of deep learning methods
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AdaResU-Net: Multiobjective adaptive convolutional neural network for medical image segmentation
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UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues
inferred← citeshttps://doi.org/10.21203/rs.3.rs-1460651/v1openalex-snapshot
Towards a comprehensive approach for characterizing cell activity in low contrast microscopic images
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