Mining neuronal morphology databases using graph transformer

Longxin Le; Jie Chen

doi:10.1117/12.3034114

13 June 2024 Mining neuronal morphology databases using graph transformer

Longxin Le, Jie Chen

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131804H (2024) https://doi.org/10.1117/12.3034114
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Neuronal morphology plays a crucial role in determining neuronal cell classification, mapping brain connectivity, and ultimately understanding the mechanisms of brain function. Currently, Neuronal morphology analyzing tasks mostly rely on traditional methods based on prior knowledge, greatly limiting the accuracy of the analysis results. To further enhance the effectiveness of neuronal morphology analysis tasks, we propose a novel graph transformer network for analyzing neuronal morphology. We tested our method on a dataset collected from Neuromorpho, and achieved better results than other methods.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Longxin Le and Jie Chen "Mining neuronal morphology databases using graph transformer", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131804H (13 June 2024); https://doi.org/10.1117/12.3034114

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