A kernel-based method for real-time markerless tumor tracking in fluoroscopic image sequence

Xiaoyong Zhang, Noriyasu Homma, Yoshihiro Takai, Yuichiro Narita, Kei Ichiji, Makoto Abe, Norihiro Sugita, Makoto Yoshizawa

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)

Abstract

This paper presents a kernel-based method for tracking tumor motion in fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). The proposed method employs a histogram-based feature space, which is robust against image deformation, to represent a tumor target in a given fluoroscopic image. The target tracking is then formulated by maximizing a Bhattacharyya coefficient that measures the similarity between the target model and target candidates in the subsequent image. The numerical solution for maximizing the Bhattacharyya coefficient is performed by a mean-shift algorithm. Experimental results demonstrate that the proposed method is superior to conventional template matching-based methods in terms of accuracy and computational cost.

Original languageEnglish
Pages828-832
Number of pages5
Publication statusPublished - 2013 Jan 1
Event2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan
Duration: 2013 Sep 142013 Sep 17

Other

Other2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013
Country/TerritoryJapan
CityNagoya
Period13/9/1413/9/17

Keywords

  • And mean-shift algorithm
  • Fluoroscopic image sequence
  • Image-guided radiation therapy (igrt)
  • Kernel density estimation
  • Real-time tumor-tracking radiation therapy (rtrt)
  • Template matching

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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