Hyperspectral imaging for perfusion assessment of the skin with convolutional neuronal networks

Matthäus Linek; Isabel Schrader; Veronika Volgger; Adrian Rühm; Ronald Sroka

doi:10.1117/12.2614462

7 December 2021 Hyperspectral imaging for perfusion assessment of the skin with convolutional neuronal networks

Matthäus Linek, Isabel Schrader, Veronika Volgger, Adrian Rühm, Ronald Sroka

Author Affiliations +

Proceedings Volume 11919, Translational Biophotonics: Diagnostics and Therapeutics; 119190C (2021) https://doi.org/10.1117/12.2614462
Event: European Conferences on Biomedical Optics, 2021, Online Only

Abstract

Convolutional neural networks were trained to determine four perfusion parameters from HSI recordings. The false-color images generated in this process show slight differences from the corresponding references, but can be reproduced meaningfully by visual assessment.

Citation Download Citation

Matthäus Linek, Isabel Schrader, Veronika Volgger, Adrian Rühm, and Ronald Sroka "Hyperspectral imaging for perfusion assessment of the skin with convolutional neuronal networks", Proc. SPIE 11919, Translational Biophotonics: Diagnostics and Therapeutics, 119190C (7 December 2021); https://doi.org/10.1117/12.2614462

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