scholarly journals Dynamic gating window technique for the reduction of dosimetric error in respiratory‐gated spot‐scanning particle therapy: An initial phantom study using patient tumor trajectory data

2020 ◽  
Vol 21 (4) ◽  
pp. 13-21
Author(s):  
Naoki Miyamoto ◽  
Kouhei Yokokawa ◽  
Seishin Takao ◽  
Taeko Matsuura ◽  
Sodai Tanaka ◽  
...  
2013 ◽  
Vol 40 (7) ◽  
pp. 071729 ◽  
Author(s):  
Taeko Matsuura ◽  
Naoki Miyamoto ◽  
Shinichi Shimizu ◽  
Yusuke Fujii ◽  
Masumi Umezawa ◽  
...  

2017 ◽  
Vol 58 (5) ◽  
pp. 710-719 ◽  
Author(s):  
Junsang Cho ◽  
Wonjoong Cheon ◽  
Sanghee Ahn ◽  
Hyunuk Jung ◽  
Heesoon Sheen ◽  
...  

Abstract Target motion–induced uncertainty in particle therapy is more complicated than that in X-ray therapy, requiring more accurate motion management. Therefore, a hybrid motion-tracking system that can track internal tumor motion and as well as an external surrogate of tumor motion was developed. Recently, many correlation tests between internal and external markers in X-ray therapy have been developed; however, the accuracy of such internal/external marker tracking systems, especially in particle therapy, has not yet been sufficiently tested. In this article, the process of installing an in-house hybrid internal/external motion-tracking system is described and the accuracy level of tracking system was acquired. Our results demonstrated that the developed in-house external/internal combined tracking system has submillimeter accuracy, and can be clinically used as a particle therapy system as well as a simulation system for moving tumor treatment.


2015 ◽  
Vol 53 (08) ◽  
Author(s):  
R Kubale ◽  
T Fuhrmann ◽  
A Arslanow ◽  
F Frenzel ◽  
P Minko ◽  
...  

2020 ◽  
Author(s):  
PF Costa ◽  
F Süßelbeck ◽  
A Bramer ◽  
M Conti ◽  
M Weber ◽  
...  

Author(s):  
SM Dudea ◽  
C Botar-Jid ◽  
D Dumitriu ◽  
A Ciurea ◽  
A Chiorean ◽  
...  

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Zuyao Zhang ◽  
Li Tang ◽  
Yifeng Wang ◽  
Xuejun Zhang

Informatica ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 33-52 ◽  
Author(s):  
Pengfei HAO ◽  
Chunlong YAO ◽  
Qingbin MENG ◽  
Xiaoqiang YU ◽  
Xu LI

2020 ◽  
Author(s):  
Jiawei Peng ◽  
Yu Xie ◽  
Deping Hu ◽  
Zhenggang Lan

The system-plus-bath model is an important tool to understand nonadiabatic dynamics for large molecular systems. The understanding of the collective motion of a huge number of bath modes is essential to reveal their key roles in the overall dynamics. We apply the principal component analysis (PCA) to investigate the bath motion based on the massive data generated from the MM-SQC (symmetrical quasi-classical dynamics method based on the Meyer-Miller mapping Hamiltonian) nonadiabatic dynamics of the excited-state energy transfer dynamics of Frenkel-exciton model. The PCA method clearly clarifies that two types of bath modes, which either display the strong vibronic couplings or have the frequencies close to electronic transition, are very important to the nonadiabatic dynamics. These observations are fully consistent with the physical insights. This conclusion is obtained purely based on the PCA understanding of the trajectory data, without the large involvement of pre-defined physical knowledge. The results show that the PCA approach, one of the simplest unsupervised machine learning methods, is very powerful to analyze the complicated nonadiabatic dynamics in condensed phase involving many degrees of freedom.


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