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AssigneeThe Regents of the University of California
InventorsAydogan Ozcan, Aniruddha Ray, Yibo Zhang, Dino Di Carlo
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A computational cytometer operates using magnetically modulated lensless speckle imaging, which introduces oscillatory motion to magnetic bead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three-dimensions (3D). Detection specificity is further enhanced through a deep learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network (P3D CNN), which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force. This compact, cost-effective and high-throughput computational cytometer can be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.
A cytometer device comprising:
A method of identifying one or more target objects among non-target objects within a sample comprising:
Dependencies are inferred from the claim text.