Human glioma tumor grading using visible resonance Raman spectroscopy and machine learning (Conference Presentation)

Binlin Wu; Yan Zhou; Shengjia Zhang; Xinguang Yu; Gangge Cheng; Ke Zhu; Cheng-hui Liu; Robert R. Alfano

doi:10.1117/12.2547054

9 March 2020 Human glioma tumor grading using visible resonance Raman spectroscopy and machine learning (Conference Presentation)

Binlin Wu, Yan Zhou, Shengjia Zhang, Xinguang Yu, Gangge Cheng, Ke Zhu, Cheng-hui Liu, Robert R. Alfano

Author Affiliations +

Proceedings Volume 11234, Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis; 112340U (2020) https://doi.org/10.1117/12.2547054
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Various machine learning algorithms will be presented to analyze spectral data collected by visible resonance Raman (VRR) spectroscopy to identify the cancer grades of human brain glioma tumors. The features were either based on selected fingerprint Raman peaks of key biomolecules, or retrieved by principal component analysis and partial least squares and artificial neural network (ANN). The grading was performed using multi-class classification using support vector machines, discriminant analysis and ANN. The most relevant features were searched using nested cross validation. The study showed VRR combined with machine learning provides a rapid robust molecular diagnostic tool for identifying cancer grades.

Conference Presentation

Citation Download Citation

Binlin Wu, Yan Zhou, Shengjia Zhang, Xinguang Yu, Gangge Cheng, Ke Zhu, Cheng-hui Liu, and Robert R. Alfano "Human glioma tumor grading using visible resonance Raman spectroscopy and machine learning (Conference Presentation)", Proc. SPIE 11234, Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis, 112340U (9 March 2020); https://doi.org/10.1117/12.2547054

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