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

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, which are robust against noise and outliers in the subsequent frames, in the tumor region of the first frame. In the subsequent frames, the key points are tracked by using a fast optical flow technique, and the tumor motion is estimated by the key points movements. To evaluate the performance, the proposed method was 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 2.46mm (1.89mm) and 1.53mm (0.38mm) 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 0.014s (0.012s) and 0.050s (0.021s) for kV and MV image sequences, respectively, and the proposed method was faster than previous methods as well as frame acquisition interval. Therefore, the proposed method has the potential for both highly accurate and fast tumor tracking in clinical applications. PMID: 30109995 [PubMed - as supplied by publisher]
Source: Physics in Medicine and Biology - Category: Physics Authors: Tags: Phys Med Biol Source Type: research