Progress in Medical Physics (한국의학물리학회지:의학물리)

Korean Society of Medical Physics (한국의학물리학회)
권호 표지

Optimization of Image Tracking Algorithm Used in 4D Radiation Therapy

4차원 방사선 치료시 영상 추적기술의 최적화

  • Park, Jong-In (Department of Biomedical Engineering, Gachon University of Medicine and Science) ;
  • Shin, Eun-Hyuk (Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Han, Young-Yih (Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Park, Hee-Chul (Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Lee, Jai-Ki (Department of Nuclear Engineering, Hanyang University) ;
  • Choi, Doo-Ho (Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine)
  • 박종인 (가천의과학대학교 의공학과) ;
  • 신은혁 (성균관대학교 의과대학 삼성서울병원 방사선종양학과) ;
  • 한영이 (성균관대학교 의과대학 삼성서울병원 방사선종양학과) ;
  • 박희철 (성균관대학교 의과대학 삼성서울병원 방사선종양학과) ;
  • 이재기 (한양대학교 원자력공학과) ;
  • 최두호 (성균관대학교 의과대학 삼성서울병원 방사선종양학과)
  • Received : 2012.01.09
  • Accepted : 2012.02.21
  • Published : 2012.03.31
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Abstract

In order to develop a Patient respiratory management system includinga biofeedback function for4-dimentional radiation therapy, this study investigated anoptimal tracking algorithmfor moving target using IR (Infra-red) camera as well as commercial camera. A tracking system was developed by LabVIEW 2010. Motion phantom images were acquired using a camera (IR or commercial). After image process were conducted to convert acquired image to binary image by applying a threshold values, several edge enhance methods such as Sobel, Prewitt, Differentiation, Sigma, Gradient, Roberts, were applied. The targetpattern was defined in the images, and acquired image from a moving targetwas tracked by matching pre-defined tracking pattern. During the matching of imagee, thecoordinateof tracking point was recorded. In order to assess the performance of tracking algorithm, the value of score which represents theaccuracy of pattern matching was defined. To compare the algorithm objectively, we repeat experiments 3 times for 5 minuts for each algorithm. Average valueand standard deviations (SD) of score were automatically calculatedsaved as ASCII format. Score of threshold only was 706, and standard deviation was 84. The value of average and SD for other algorithms which combined edge detection method and thresholdwere 794, 64 in Sobel, 770, 101 in Differentiation, 754, 85 in Gradient, 763, 75 in Prewitt, 777, 93 in Roberts, and 822, 62 in Sigma, respectively. According to score analysis, the most efficient tracking algorithm is the Sigma method. Therefore, 4-dimentional radiation threapy is expected tobemore efficient if threshold and Sigma edge detection method are used together in target tracking.

4차원 방사선치료시 환자의 정확한 호흡 조절을 위한 바이오피드백 시스템의 개발을 위해 IR (Infra-red) 카메라 뿐만아니라 일반 카메라에서 얻는 영상에서 표적의 움직임을 추적하는 최적화된 추적 알고리즘을 찾고자 한다. 본 연구에서는 LabVIEW 2010을 사용해서 시스템을 구성하였다. 모션팬톰(motimo Phantom)의 움직임을 카메라 (IR 카메라와 일반 카메라)를 통하여 영상을 획득하고 영상처리를 거친 후 ROI (Region of interest)를 설정하여, 영상에서 지정한 ROI와 패턴 매치된 점의 상하의 움직임만 좌표로 기록하였다. 영상처리에는 문턱값을 사용하여 이진화된 영상을 만들고 Sobel, Prewitt, Differentiation, Sigma, Gradient, Roberts 등의 여러 윤곽선 강조방법들을 적용한 후에 영상을 합하여 사용했다. 다양한 방법들의 성능을 객관적으로 평가하기 위한 인자로 'score' 값을 정의하여 성능을 비교하였다. 모든 방법들을 최대한 같은 조건에서 비교하기 위해서 5분씩 3번 반복하여 측정하여 ASCII 파일로 저장하여 저장된 'score' 값의 평균값과 표준편차를 구하여 비교하였다. 문턱값만을 적용한 영상의 score는 706이고 표준편차는 84였다. 윤곽선강조를 사용한 알고리즘들의 score와 표준편차는 각각 Sobel 794와 64, Differentiation 770과 101, Gradient는 754과 85, Prewitt 763과 75, Roberts 777와 93, Sigma 822와 62였다. 가장 좋은 효율을 보인 알고리즘은 Sigma방법이였다. 추적 효율이 가장 좋게 나온 Sigma방법을 이용해서 호흡을 조절하여 호흡동조 방사선치료를 시행할 때 카메라(IR 카메라 및 일반 카메라)상의 점 추적에 대한 정확도의 증가로 치료 효율을 높일 수 있을 것이라 기대된다.

Keywords

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