Single-Particle Tracking by Graph Transformer
Satoshi Kamiya, Kazuhiro Hotta, Taka-aki Tsunoyama, Akihiro Kusumi
Abstract
The immune system has been studied extensively by increasing the demand for object tracking of particles. However, because researches on single-particle tracking (SPT) by machine learning have not progressed yet, currently there is a reliance on software analysis despite low accuracy. There are three problems with SPT. First, there are no differences in the feature of each molecule, so tracking by feature differences is not possible. Second, it is difficult to predict the direction of molecular motion because it is random. Third, the high density of molecules causes frequent ID switches. Therefore, we propose Particle Tracking via Graph Transformer (PTGT), which takes into account the relationships among molecules, to solve these problems.
BibTeX
@inproceedings{icassp2023_singleparticletr,
title = {Single-Particle Tracking by Graph Transformer},
author = {Satoshi Kamiya and Kazuhiro Hotta and Taka-aki Tsunoyama and Akihiro Kusumi},
booktitle = {ICASSP 2023},
year = {2023}
}