A key-point based real-time tracking of lung tumor in x-ray image sequence by using difference of Gaussians filtering and optical flow

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F18%3A00329538" target="_blank" >RIV/68407700:21220/18:00329538 - isvavai.cz</a>

Výsledek na webu

<a href="https://iopscience.iop.org/article/10.1088/1361-6560/aada71/meta" target="_blank" >https://iopscience.iop.org/article/10.1088/1361-6560/aada71/meta</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1361-6560/aada71" target="_blank" >10.1088/1361-6560/aada71</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A key-point based real-time tracking of lung tumor in x-ray image sequence by using difference of Gaussians filtering and optical flow

Popis výsledku v původním jazyce

In radiation therapy, for accurate radiation dose delivery to a target tumor and reduction of the extra exposure of normal tissues, real-time tumor tracking is typically an important technique in lung cancer treatment since lung tumors move with patients' respiration. To observe a tumor motion in real time, x-ray fluoroscopic devices can be employed, and various tracking techniques have been proposed to track tumors. However, development of a fast and accurate tracking method for clinical use is still a challenging task since the obscured image of the tumor can cause decreased tracking accuracy and can result in additional processing time for remedying the accuracy. In this study, a new key-point-based tumor tracking method, which is sufficiently fast and accurate, is presented. Given an x-ray image sequence, the proposed method employs a difference-of-Gaussians filtering technique to detect key points in the tumor region of the first frame which are robust against noise and outliers in the subsequent frames. In the subsequent frames, these key points are tracked using a fast optical flow technique, and tumor motion is estimated via their movement. To evaluate the performance, the proposed method has been tested on several clinical kV and MV x-ray image sequences. The experimental results showed that the average of the root mean square errors of tracking were 2.46 mm (1.89 mm) and 1.53 mm (0.38 mm) for kV and MV x-ray image sequences, respectively. This tracking performance was more accurate than previous tracking methods. In addition, the average processing times for each frame were 0.014 s (0.012 s) and 0.050 s (0.021 s) for kV and MV image sequences, respectively, and the proposed method was faster than previous methods as well as shorter than frame acquisition interval. Therefore, the proposed method has the potential for both highly accurate and fast tumor tracking in clinical applications.

Název v anglickém jazyce

A key-point based real-time tracking of lung tumor in x-ray image sequence by using difference of Gaussians filtering and optical flow

Popis výsledku anglicky

In radiation therapy, for accurate radiation dose delivery to a target tumor and reduction of the extra exposure of normal tissues, real-time tumor tracking is typically an important technique in lung cancer treatment since lung tumors move with patients' respiration. To observe a tumor motion in real time, x-ray fluoroscopic devices can be employed, and various tracking techniques have been proposed to track tumors. However, development of a fast and accurate tracking method for clinical use is still a challenging task since the obscured image of the tumor can cause decreased tracking accuracy and can result in additional processing time for remedying the accuracy. In this study, a new key-point-based tumor tracking method, which is sufficiently fast and accurate, is presented. Given an x-ray image sequence, the proposed method employs a difference-of-Gaussians filtering technique to detect key points in the tumor region of the first frame which are robust against noise and outliers in the subsequent frames. In the subsequent frames, these key points are tracked using a fast optical flow technique, and tumor motion is estimated via their movement. To evaluate the performance, the proposed method has been tested on several clinical kV and MV x-ray image sequences. The experimental results showed that the average of the root mean square errors of tracking were 2.46 mm (1.89 mm) and 1.53 mm (0.38 mm) for kV and MV x-ray image sequences, respectively. This tracking performance was more accurate than previous tracking methods. In addition, the average processing times for each frame were 0.014 s (0.012 s) and 0.050 s (0.021 s) for kV and MV image sequences, respectively, and the proposed method was faster than previous methods as well as shorter than frame acquisition interval. Therefore, the proposed method has the potential for both highly accurate and fast tumor tracking in clinical applications.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20301 - Mechanical engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Physics in Medicine and Biology

ISSN

0031-9155

e-ISSN

1361-6560

Svazek periodika

63

Číslo periodika v rámci svazku

18

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

16

Strana od-do

—

Kód UT WoS článku

000444345400007

EID výsledku v databázi Scopus

2-s2.0-85054821969