Deep learning-based computational cytometer using magnetically-modulated coherent imaging

Tairan Liu; Yibo Zhang; Mengxing Ouyang; Aniruddha Ray; 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 C. Koydemir; Omai B. Garner; Dino Di Carlo; Aydogan Ozcan

doi:10.1117/12.2579828

5 March 2021 Deep learning-based computational cytometer using magnetically-modulated coherent imaging

Tairan Liu, Yibo Zhang, Mengxing Ouyang, Aniruddha Ray, 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 C. Koydemir, Omai B. Garner, Dino Di Carlo, Aydogan Ozcan

Author Affiliations +

Proceedings Volume 11632, Optics and Biophotonics in Low-Resource Settings VII; 116320I (2021) https://doi.org/10.1117/12.2579828
Event: SPIE BiOS, 2021, Online Only

Abstract

We present a deep learning-based high-throughput cytometer to detect rare cells in whole blood using a cost-effective and light-weight design. This system uses magnetic-particles to label and enrich the target cells. Then, a periodically-alternating magnetic-field creates time-modulated diffraction patterns of the target cells that are recorded using a lensless microscope. Finally, a custom-designed convolutional network is used to detect and classify the target cells based on their modulated spatio-temporal patterns. This cytometer was tested with cancer cells spiked in whole blood to achieve a limit-of-detection of 10 cells/mL. This compact, cost-effective and high-throughput cytometer might serve diagnostics needs in resource-limited-settings.

Conference Presentation

Citation Download Citation

Tairan Liu, Yibo Zhang, Mengxing Ouyang, Aniruddha Ray, 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 C. Koydemir, Omai B. Garner, Dino Di Carlo, and Aydogan Ozcan "Deep learning-based computational cytometer using magnetically-modulated coherent imaging", Proc. SPIE 11632, Optics and Biophotonics in Low-Resource Settings VII, 116320I (5 March 2021); https://doi.org/10.1117/12.2579828

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available