Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning

Xianxu Zeng; Xiaoan Zhang; Tao Xu; Canyu Li; Xiaofang Wang; Jason Jerwick; Yuan Ning; Yihong Wang; Linlin Zhang; Zhan Zhang; Yutao Ma; Chao Zhou

Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning

Xianxu Zeng, Xiaoan Zhang, Tao Xu, Canyu Li, Xiaofang Wang, Jason Jerwick, Yuan Ning, Yihong Wang, Linlin Zhang, Zhan Zhang, Yutao Ma, Chao Zhou

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

Abstract

Current tools for cervical cancer screening cannot provide real-time results or localize suspicious regions. Label-free optical coherence microscopy combined with a machine learning algorithm shows great potential to provide real-time diagnosis of human cervical diseases.

Original language	English
Title of host publication	Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018
Publisher	Optica Publishing Group (formerly OSA)
ISBN (Print)	9781943580453
State	Published - 2018
Event	Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018 - Hong Kong, China Duration: Jul 29 2018 → Aug 3 2018

Publication series

Name	Optics InfoBase Conference Papers
Volume	Part F113-CLEOPR 2018
ISSN (Electronic)	2162-2701

Conference

Conference	Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018
Country/Territory	China
City	Hong Kong
Period	07/29/18 → 08/3/18

Cite this

Zeng, X., Zhang, X., Xu, T., Li, C., Wang, X., Jerwick, J., Ning, Y., Wang, Y., Zhang, L., Zhang, Z., Ma, Y., & Zhou, C. (2018). Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning. In Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018 (Optics InfoBase Conference Papers; Vol. Part F113-CLEOPR 2018). Optica Publishing Group (formerly OSA).

@inproceedings{ab234b4652194fab9c184cf85c7b95f1,

title = "Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning",

abstract = "Current tools for cervical cancer screening cannot provide real-time results or localize suspicious regions. Label-free optical coherence microscopy combined with a machine learning algorithm shows great potential to provide real-time diagnosis of human cervical diseases.",

author = "Xianxu Zeng and Xiaoan Zhang and Tao Xu and Canyu Li and Xiaofang Wang and Jason Jerwick and Yuan Ning and Yihong Wang and Linlin Zhang and Zhan Zhang and Yutao Ma and Chao Zhou",

note = "Publisher Copyright: {\textcopyright} OSA 2018; Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018 ; Conference date: 29-07-2018 Through 03-08-2018",

year = "2018",

language = "English",

isbn = "9781943580453",

series = "Optics InfoBase Conference Papers",

publisher = "Optica Publishing Group (formerly OSA)",

booktitle = "Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018",

}

Zeng, X, Zhang, X, Xu, T, Li, C, Wang, X, Jerwick, J, Ning, Y, Wang, Y, Zhang, L, Zhang, Z, Ma, Y & Zhou, C 2018, Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning. in Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018. Optics InfoBase Conference Papers, vol. Part F113-CLEOPR 2018, Optica Publishing Group (formerly OSA), Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018, Hong Kong, China, 07/29/18.

Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning. / Zeng, Xianxu; Zhang, Xiaoan; Xu, Tao et al.
Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018. Optica Publishing Group (formerly OSA), 2018. (Optics InfoBase Conference Papers; Vol. Part F113-CLEOPR 2018).

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

TY - GEN

T1 - Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning

AU - Zeng, Xianxu

AU - Zhang, Xiaoan

AU - Xu, Tao

AU - Li, Canyu

AU - Wang, Xiaofang

AU - Jerwick, Jason

AU - Ning, Yuan

AU - Wang, Yihong

AU - Zhang, Linlin

AU - Zhang, Zhan

AU - Ma, Yutao

AU - Zhou, Chao

PY - 2018

Y1 - 2018

N2 - Current tools for cervical cancer screening cannot provide real-time results or localize suspicious regions. Label-free optical coherence microscopy combined with a machine learning algorithm shows great potential to provide real-time diagnosis of human cervical diseases.

AB - Current tools for cervical cancer screening cannot provide real-time results or localize suspicious regions. Label-free optical coherence microscopy combined with a machine learning algorithm shows great potential to provide real-time diagnosis of human cervical diseases.

UR - http://www.scopus.com/inward/record.url?scp=85059383048&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85059383048

SN - 9781943580453

T3 - Optics InfoBase Conference Papers

BT - Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018

PB - Optica Publishing Group (formerly OSA)

T2 - Conference on Lasers and Electro-Optics/Pacific Rim, CLEOPR 2018

Y2 - 29 July 2018 through 3 August 2018

ER -

Label-free Diagnosis of Cervical Cancer based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning

Abstract

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