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 proceedingConference contributionpeer-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 languageEnglish
Title of host publication2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781943580453
DOIs
StatePublished - Jul 2 2018
Event2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018 - Wanchai, Hong Kong
Duration: Jul 29 2018Aug 3 2018

Publication series

Name2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018

Conference

Conference2018 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2018
Country/TerritoryHong Kong
CityWanchai
Period07/29/1808/3/18

Fingerprint

Dive into the research topics of 'Label-Free Diagnosis of Cervical Cancer Based on Ultrahigh Resolution Optical Coherence Microscopy and Machine Learning'. Together they form a unique fingerprint.

Cite this