@inproceedings{36273c782e3545cd8ce8045f055b259d,
title = "Real-time colorectal cancer diagnosis using PR-OCT with deep learning",
abstract = "A pattern-recognition optical coherence tomography was designed to automate diagnosis of human colorectal tissue in real-time. An area under the ROC of 0.998 is achieved by our initial experience with 18 ex vivo human specimens.",
author = "Yifeng Zeng and Shiqi Xu and Chapman, {William C.} and Shuying Li and Zahra Alipour and Heba Abdelal and Deyali Chatterjee and Matthew Mutch and Quing Zhu",
note = "Funding Information: The authors acknowledge the funding support of R01CA228047(QZ) and T32CA009621(WC). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Publisher Copyright: {\textcopyright} OSA 2020 {\textcopyright} 2020 The Author(s).; Optical Coherence Tomography, OCT 2020 ; Conference date: 20-04-2020 Through 23-04-2020",
year = "2020",
language = "English (US)",
series = "Optics InfoBase Conference Papers",
publisher = "OSA - The Optical Society",
booktitle = "Optical Coherence Tomography, OCT 2020",
}