Megavoltage Cone-beam CT 영상의 변환을 이용한 변환 영상 정합의 정확도 향상

Enhancement of the Deformable Image Registration Accuracy Using Image Modification of MV CBCT

  • 김민주 (가톨릭대학교 의과대학 의공학교실) ;
  • 장지나 (가톨릭대학교 의과대학 의공학교실) ;
  • 박소현 (가톨릭대학교 의과대학 의공학교실) ;
  • 김태호 (가톨릭대학교 의과대학 의공학교실) ;
  • 강영남 (가톨릭대학교 의과대학 서울 성모병원 방사선 종양학과) ;
  • 서태석 (가톨릭대학교 의과대학 의공학교)
  • Kim, Min-Joo (Department of Biomedical Engineering, The Catholic University of Korea) ;
  • Chang, Ji-Na (Department of Biomedical Engineering, The Catholic University of Korea) ;
  • Park, So-Hyun (Department of Biomedical Engineering, The Catholic University of Korea) ;
  • Kim, Tae-Ho (Department of Biomedical Engineering, The Catholic University of Korea) ;
  • Kang, Young-Nam (Department of Radiation Oncology, Seoul St. Mary's Hospital, The Catholic University of Korea) ;
  • Suh, Tae-Suk (Department of Biomedical Engineering, The Catholic University of Korea)
  • 투고 : 2010.12.28
  • 심사 : 2011.03.02
  • 발행 : 2011.03.31

초록

적응 방사선 치료(Adaptive Radiation Therapy, ART)를 실행하기 위한 고도의 정확성을 갖는 변형 영상 정합 방법은 필수이다. 본 연구의 목적은 Megavoltage cone-beam CT (MV CBCT)영상의 Intensity 변화를 통한 영상 정합의 정확성의 향상이다. Intensity 변화 값을 도출 하기 위해 kilovoltage CT (kV CT)와 MV CBCT를 이용하여 12 종류의 전자 밀도 바를 제공하는 Cheese 팬텀의영상을 획득하고, 영상들로부터 kV CT와 MV CBCT의 Hounsfield Unit (HU)값들의 관계를 도출하였다. MV CBCT 영상의 잡음을 감소하기 위해 Gaussian smoothing 필터를 적용하였다. MV CBCT영상의 intensity는 마치 동일한 모달리티에서 획득된 영상과 같은 kV CT와 동일한 범위의 intensity로 변화시켰다. 이후 두 영상에 효율적이고 사용하기 쉬운 intensity 기반의 데몬 영상 정합이 적용되었다. 본 연구실에서 인체 내 폐를 모사하도록 제작된 변형 폐 팬텀을 이용하여 위와 같은 방법을 적용하여 영상 정합을 하였다. Cheese 팬텀 영상, 변형 폐 팬텀 영상을 이용한 변형영상 정합 결과는 상관 계수가 각각 6.07%, 18% 향상되었다. 변형 폐 팬텀 영상의 변형 영상 정합 정확성을 평가하기 위해 추가적으로 측정된 팬텀 내부에 삽입한 표적의 중심 좌표를 이용하여vector 차이를 계산하였다. 벡터 차이는 $2.23{\pm}1.19mm$, $1.39{\pm}0.97mm$였다. 본 연구에서 사용한 intensity 변화 방법을 통해 변형 영상 정합의 정확성이 향상됨을 확인 하였고, 본 연구는 영상 정합 정확성을 향상시키기 위한 해결 방법이 될 수 있다. 차후 연구 계획도 본 연구 내용에 의해 제안되었다.

To perform the Adaptive Radiation Therapy (ART), a high degree of deformable registration accuracy is essential. The purpose of this study is to identify whether the change of MV CBCT intensity can improve registration accuracy using predefined modification level and filtering process. To obtain modification level, the cheese phantom images was acquired from both kilovoltage CT (kV CT), megavoltage cone-beam CT (MV CBCT). From the cheese phantom images, the modification level of MV CBCT was defined from the relationship between Hounsfield Units (HUs) of kV CT and MV CBCT images. 'Gaussian smoothing filter' was added to reduce the noise of the MV CBCT images. The intensity of MV CBCT image was changed to the intensity of the kV CT image to make the two images have the same intensity range as if they were obtained from the same modality. The demon deformable registration which was efficient and easy to perform the deformable registration was applied. The deformable lung phantom which was intentionally created in the laboratory to imitate the changes of the breathing period was acquired from kV CT and MV CBCT. And then the deformable lung phantom images were applied to the proposed method. As a result of deformable image registration, the similarity of the correlation coefficient was used for a quantitative evaluation of the result was increased by 6.07% in the cheese phantom, and 18% in the deformable lung phantom. For the additional evaluation of the registration of the deformable lung phantom, the centric coordinates of the mark which was inserted into the inner part of the phantom were measured to calculate the vector difference. The vector differences from the result were 2.23, 1.39 mm with/without modification of intensity of MV CBCT images, respectively. In summary, our method has quantitatively improved the accuracy of deformable registration and could be a useful solution to improve the image registration accuracy. A further study was also suggested in this paper.

키워드

참고문헌

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