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T cells sense biophysical cues using lamellipodia and filopodia to optimize intraluminal path finding

, , , , , , and . Integr. Biol., (2014)
DOI: 10.1039/C4IB00021H

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Quantitative Phase Imaging and Artificial Intelligence: A Review., , , , , , and . CoRR, (2018)Speckle-Correlation Scattering Matrix Approaches for Imaging and Sensing through Turbidity., , , and . Sensors, 20 (11): 3147 (2020)DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging Using Deep Learning., , , , , , , , , and 1 other author(s). IEEE Trans. Medical Imaging, 40 (5): 1508-1518 (2021)Deep-Learning-Based Label-Free Segmentation of Cell Nuclei in Time-Lapse Refractive Index Tomograms., , , , , , , , and . IEEE Access, (2019)Missing Cone Artifact Removal in ODT Using Unsupervised Deep Learning in the Projection Domain., , , , and . IEEE Trans. Computational Imaging, (2021)Quantitative Phase Imaging Techniques for the Study of Cell Pathophysiology: From Principles to Applications., , , , , , , , , and . Sensors, 13 (4): 4170-4191 (2013)T cells sense biophysical cues using lamellipodia and filopodia to optimize intraluminal path finding, , , , , , and . Integr. Biol., (2014)Unsupervised Missing Cone Deep Learning in Optical Diffraction Tomography., , , , and . CoRR, (2021)Roadmap on Digital Holography-Based Quantitative Phase Imaging., , , , , , , , , and 7 other author(s). J. Imaging, 7 (12): 252 (2021)