Deep learning correlates single-cell morphology with migratory behaviors in microfluidics

Zhixiong Zhang; Lili Chen; Yu Chih Chen; Euisik Yoon

Deep learning correlates single-cell morphology with migratory behaviors in microfluidics

Zhixiong Zhang, Lili Chen, Yu Chih Chen, Euisik Yoon

Yonsei Advanced Science Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Metastasis is the major cause of death in breast cancer patients, yet it remains challenging to pinpoint metastatic cancer cells. In this work, we present a comprehensive morphological analysis using deep learning methods including Random Decision Forest (RDF) and Artificial Neural Network (ANN) to establish the correlation between cellular morphology and migration direction/speed.

Original language	English
Title of host publication	22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018
Publisher	Chemical and Biological Microsystems Society
Pages	331-332
Number of pages	2
ISBN (Electronic)	9781510897571
Publication status	Published - 2018
Event	22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018 - Kaohsiung, Taiwan, Province of China Duration: 2018 Nov 11 → 2018 Nov 15

Publication series

Name	22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018
Volume	1

Conference

Conference	22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018
Country/Territory	Taiwan, Province of China
City	Kaohsiung
Period	18/11/11 → 18/11/15

Bibliographical note

Publisher Copyright:
Copyright© (2018) by Chemical and Biological Microsystems Society.All rights reserved.

All Science Journal Classification (ASJC) codes

Chemistry(all)
Bioengineering
Chemical Engineering (miscellaneous)
Control and Systems Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

Zhang, Z., Chen, L., Chen, Y. C., & Yoon, E. (2018). Deep learning correlates single-cell morphology with migratory behaviors in microfluidics. In 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018 (pp. 331-332). (22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018; Vol. 1). Chemical and Biological Microsystems Society.

Zhang, Zhixiong ; Chen, Lili ; Chen, Yu Chih et al. / Deep learning correlates single-cell morphology with migratory behaviors in microfluidics. 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018. Chemical and Biological Microsystems Society, 2018. pp. 331-332 (22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018).

@inproceedings{72468ee8df254e6a9d4ae3fd981d7a6a,

title = "Deep learning correlates single-cell morphology with migratory behaviors in microfluidics",

abstract = "Metastasis is the major cause of death in breast cancer patients, yet it remains challenging to pinpoint metastatic cancer cells. In this work, we present a comprehensive morphological analysis using deep learning methods including Random Decision Forest (RDF) and Artificial Neural Network (ANN) to establish the correlation between cellular morphology and migration direction/speed.",

author = "Zhixiong Zhang and Lili Chen and Chen, {Yu Chih} and Euisik Yoon",

note = "Publisher Copyright: Copyright{\textcopyright} (2018) by Chemical and Biological Microsystems Society.All rights reserved.; 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018 ; Conference date: 11-11-2018 Through 15-11-2018",

year = "2018",

language = "English",

series = "22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018",

publisher = "Chemical and Biological Microsystems Society",

pages = "331--332",

booktitle = "22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018",

}

Zhang, Z, Chen, L, Chen, YC & Yoon, E 2018, Deep learning correlates single-cell morphology with migratory behaviors in microfluidics. in 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018. 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018, vol. 1, Chemical and Biological Microsystems Society, pp. 331-332, 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018, Kaohsiung, Taiwan, Province of China, 18/11/11.

Deep learning correlates single-cell morphology with migratory behaviors in microfluidics. / Zhang, Zhixiong; Chen, Lili; Chen, Yu Chih et al.

22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018. Chemical and Biological Microsystems Society, 2018. p. 331-332 (22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Deep learning correlates single-cell morphology with migratory behaviors in microfluidics

AU - Zhang, Zhixiong

AU - Chen, Lili

AU - Chen, Yu Chih

AU - Yoon, Euisik

PY - 2018

Y1 - 2018

N2 - Metastasis is the major cause of death in breast cancer patients, yet it remains challenging to pinpoint metastatic cancer cells. In this work, we present a comprehensive morphological analysis using deep learning methods including Random Decision Forest (RDF) and Artificial Neural Network (ANN) to establish the correlation between cellular morphology and migration direction/speed.

AB - Metastasis is the major cause of death in breast cancer patients, yet it remains challenging to pinpoint metastatic cancer cells. In this work, we present a comprehensive morphological analysis using deep learning methods including Random Decision Forest (RDF) and Artificial Neural Network (ANN) to establish the correlation between cellular morphology and migration direction/speed.

UR - http://www.scopus.com/inward/record.url?scp=85079862972&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85079862972&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85079862972

T3 - 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018

SP - 331

EP - 332

BT - 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018

PB - Chemical and Biological Microsystems Society

T2 - 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018

Y2 - 11 November 2018 through 15 November 2018

ER -

Zhang Z, Chen L, Chen YC, Yoon E. Deep learning correlates single-cell morphology with migratory behaviors in microfluidics. In 22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018. Chemical and Biological Microsystems Society. 2018. p. 331-332. (22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018).

Deep learning correlates single-cell morphology with migratory behaviors in microfluidics

Abstract

Publication series

Conference

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

Other files and links

Fingerprint

Cite this