Pixel-wise and real-time estimation of optical mean path length using deep learning: application for intraoperative functional brain mapping

Charly Caredda; Ivan Ezhov; Michaël Sdika; Frédéric Lange; Luca Giannoni; Ilias Tachtsidis; Bruno Montcel

doi:10.1117/12.3016632

6 June 2024 Pixel-wise and real-time estimation of optical mean path length using deep learning: application for intraoperative functional brain mapping

Charly Caredda, Ivan Ezhov, Michaël Sdika, Frédéric Lange, Luca Giannoni, Ilias Tachtsidis, Bruno Montcel

Author Affiliations +

Proceedings Volume 13009, Clinical Biophotonics III; 130090F (2024) https://doi.org/10.1117/12.3016632
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Conference Poster

Abstract

Optical imaging is a non-invasive technique that is able to monitor hemodynamic and metabolic brain response following neuronal activation during neurosurgery. However, it still lacks robustness to be used as a clinical standard. In particular, the quantification of the biomarkers of brain functionality needs to be improved. The quantification relies on the modified Beer Lambert law, which needs a correct estimation of the optical mean path length of traveled photons. Monte Carlo simulations are used for estimating the optical path length, but it is time-consuming, especially when modeling a patient’s brain cortex. In this study, we developed a neural network based on the UNET architecture for a pixel-wise and real-time estimation of optical mean path length. The neural network was trained with segmentation of brain cortex as input and mean path length data as target. This deep learning approach allows a real time estimation of the optical mean path length. The results can be beneficial and useful within the framework of our EU-funded HyperProbe project, which aims at transforming neuronavigation during glioma resection using novel hyperspectral imaging technology.

Citation Download Citation

Charly Caredda, Ivan Ezhov, Michaël Sdika, Frédéric Lange, Luca Giannoni, Ilias Tachtsidis, and Bruno Montcel "Pixel-wise and real-time estimation of optical mean path length using deep learning: application for intraoperative functional brain mapping", Proc. SPIE 13009, Clinical Biophotonics III, 130090F (6 June 2024); https://doi.org/10.1117/12.3016632

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