Single fiber OCT imager for breast tissue classification based on deep learning

Yuwei Liu; Basil Hubbi; Xuan Liu

doi:10.1117/12.2547015

20 February 2020 Single fiber OCT imager for breast tissue classification based on deep learning

Yuwei Liu, Basil Hubbi, Xuan Liu

Proceedings Volume 11233, Optical Fibers and Sensors for Medical Diagnostics and Treatment Applications XX; 1123313 (2020) https://doi.org/10.1117/12.2547015
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

We investigated a deep learning strategy to analyze optical coherence tomography image for accurate tissue characterization based on a single fiber OCT probe. We obtained OCT data from human breast tissue specimens. Using OCT data obtained from adipose breast tissue (normal tissue) and diseased tissue as confirmed in histology, we trained and validated a convolutional neural network (CNN) for accurate breast tissue classification. We demonstrated tumor margin identification based CNN classification of tissue at different spatial locations. We further demonstrated CNN tissue classification in OCT imaging based on a manually scanned single fiber probe. Our results demonstrated that OCT imaging capability integrated into a low-cost, disposable single fiber probe, along with sophisticated deep learning algorithms for tissue classification, allows minimally invasive tissue characterization, and can be used for cancer diagnosis or surgical margin assessment.

Conference Presentation

Citation Download Citation

Yuwei Liu, Basil Hubbi, and Xuan Liu "Single fiber OCT imager for breast tissue classification based on deep learning", Proc. SPIE 11233, Optical Fibers and Sensors for Medical Diagnostics and Treatment Applications XX, 1123313 (20 February 2020); https://doi.org/10.1117/12.2547015

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