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Computational cytometer based on magnetically modulated coherent imaging and deep learning

Light(Science & Applications) 2019年第1期8卷 385-399页

作者： Yibo Zhang mengxing ouyang Aniruddha Ray Tairan Liu Janay Kong Bijie Bai Donghyuk Kim Alexander Guziak Yi Luo Alborz Feizi Katherine Tsai Zhuoran Duan Xuewei Liu Danny Kim Chloe Cheung Sener Yalcin Hatice Ceylan Koydemir Omai B.Garner Dino Di Carlo Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Department of Bioengineering University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute University of CaliforniaLos AngelesCA 90095USA Department of Physics and Astronomy University of ToledoToledoOH 43606USA Department of Physics and Astronomy University of CaliforniaLos AngelesCA 90095USA Yale School of Medicine New HavenCT 06510USA Department of Biochemistry University of CaliforniaLos AngelesCA 90095USA Department of Pathology and Laboratory Medicine University of CaliforniaLos AngelesCA 90095USA Department of Mechanical and Aerospace Engineering University of CaliforniaLos AngelesCA 90095USA Jonsson Comprehensive Cancer Center University of CaliforniaLos AngelesCA 90095USA Department of Surgery David Geffen School of MedicineUniversity of CaliforniaLos AngelesCA 90095USA

Detecting rare cells within blood has numerous applications in disease *** rare cell detection techniques are typically hindered by their high cost and low ***,we present a computational cytometer based on magnetically modulated lensless speckle imaging,which introduces oscillatory motion to the magneticbead-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).In addition to using cell-specific antibodies to magnetically label target cells,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 *** demonstrate the performance of this technique,we built a high-throughput,compact and cost-effective prototype for detecting MCF7 cancer cells spiked in whole blood *** serial dilution experiments,we quantified the limit of detection(LoD)as 10 cells per millilitre of whole blood,which could be further improved through multiplexing parallel imaging channels within the same *** compact,cost-effective and high-throughput computational cytometer can potentially be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.

关键词： rare magnetic speckle

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