Mr. Alon Pener-Tessler Profile

Alon Pener-Tessler

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 13 March 2024 Poster + Paper

Deep learning architectures for spatial-frequency 3D fluorescence in oral cancer surgery models

Natalie Won, Anjolaluawa Adewale, Jerry Wan, Mandolin Bartling, Jason Townson, Harley Chan, Esmat Najjar, Alon Pener-Tessler, Brian Wilson, Jonathan Irish, Michael Daly

Proceedings Volume 12825, 128250D (2024) https://doi.org/10.1117/12.3002880

KEYWORDS: Fluorescence, 3D modeling, Surgery, Cancer, Deep learning, Optical properties, Spatial frequencies

Read Abstract +

Fluorescence-guided surgery systems employed during oral cancer resection help detect the lateral margin yet fail to quantify the deep margins of the tumor prior to resection. Without comprehensive quantification of three-dimensional tumor margins, complete resection remains challenging. While interoperative techniques to assess the deep margin exist, they are limited in precision, leaving an unmet need for a system that can quantify depth. Our group is developing a deep learning (DL)-enabled fluorescence spatial frequency domain imaging (SFDI) system to address this limitation. The SFDI system captures fluorescence (F) and reflectance (R) images that contain information on tissue optical properties (OP) and depth sensitivity across spatial frequencies. Coupling DL with SFDI imaging allows for the near-real time construction of depth and concentration maps. Here, we compare three DL architectures that use SFDI images as inputs: i) F+OP, where OP (absorption and scattering) are obtained analytically from reflectance images; ii) F+R; iii) F/R. Training the three models required 10,000 tumor samples; synthetic tumors derived from composite spherical harmonics circumvented the need for patient data. The synthetic tumors were passed to a diffusion-theory light propagation model to generate a dataset of artificial SFDI images for DL training. Two oral cancer models derived from MRI of patient tongue tumors are used to evaluate DL performance in: i) in silico SFDI images ii) optical phantoms. These studies evaluate how system performance is affected by the SFDI input data and DL architectures. Future studies are required to assess system performance in vivo.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

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

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years