A kernel-based method for markerless tumor tracking in kV fluoroscopic images

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

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

Markerless tracking of respiration-induced tumor motion in kilo-voltage (kV) fluoroscopic image sequence is still a challenging task in real time image-guided radiation therapy (IGRT). Most of existing markerless tracking methods are based on a template matching technique or its extensions that are frequently sensitive to non-rigid tumor deformation and involve expensive computation. This paper presents a kernel-based method that is capable of tracking tumor motion in kV fluoroscopic image sequence with robust performance and low computational cost. The proposed tracking system consists of the following three steps. To enhance the contrast of kV fluoroscopic image, we firstly utilize a histogram equalization to transform the intensities of original images to a wider dynamical intensity range. A tumor target in the first frame is then represented by using a histogram-based feature vector. Subsequently, the target tracking is then formulated by maximizing a Bhattacharyya coefficient that measures the similarity between the tumor target and its candidates in the subsequent frames. The numerical solution for maximizing the Bhattacharyya coefficient is performed by a mean-shift algorithm. The proposed method was evaluated by using four clinical kV fluoroscopic image sequences. For comparison, we also implement four conventional template matching-based methods and compare their performance with our proposed method in terms of the tracking accuracy and computational cost. Experimental results demonstrated that the proposed method is superior to conventional template matching-based methods.

Original languageEnglish
Article number4897
Pages (from-to)4897-4911
Number of pages15
JournalPhysics in medicine and biology
Volume59
Issue number17
DOIs
Publication statusPublished - 2014 Sep 7

Keywords

  • computer vision
  • markerless tumor tracking
  • mean shift algorithm
  • radiation therapy

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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