대한방사선기술학회지:방사선기술과학 (Journal of radiological science and technology)

  • 제39권2호
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  • Pages.227-236
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  • 2016
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  • 2288-3509(pISSN)
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  • 2384-1168(eISSN)
대한방사선과학회 (Korean Society of Radiological Science)
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특이값 분해 기반 Dynamic PET 영상의 노이즈 제거 기법 : 예비 연구

Singular Value Decomposition based Noise Reduction Technique for Dynamic PET I mage : Preliminary study

  • 편도영 (동서대학교 보건과학과) ;
  • 김정수 (동남보건대학교 방사선과) ;
  • 백철하 (동서대학교 보건과학과) ;
  • 정영진 (동서대학교 보건과학과)
  • 투고 : 2016.04.30
  • 심사 : 2016.06.18
  • 발행 : 2016.06.30
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초록

동적 양전자방출단층 촬영은 3차원의 공간적 정보와 추가적인 1차원의 시계열 정보가 함께 존재하는 시공간 정보(4차원)의 데이터를 활용할 수 있어서 전통적인 영상기법에 비해 임상 진단 및 분석에 활용할 수 있는 정보의 양이 급격히 증가된 의료영상 촬영기법이다. 그러나, 인체에 주입할 수 있는 방사성 동위원소의 양의 제한 및 검출기 특징에 따른 감마선 검출의 제한 등이 영상을 재구성 하는 것에 제약사항으로 존재하여, 고화질 의료 영상의 획득에 어려움이 존재하여 임상적 활용의 제한사항이 되어왔다. 본 연구에서는, 4차원 영상의 적극적인 임상 활용을 위해서 영상의 화질을 개선하고 정량적인 평가를 할 수 있는 영상 기법을 연구하였다. 이를 위해, Matlab을 이용하여 영상의 여러 독립적인 신호원을 분리하여 영상의 신호와 노이즈로 구분할 수 있도록, 선형 대수학의 기법 중 하나인 특이값 분해를 활용하였다. 이를 통해, 개선된 동적 양전자방출단층 영상은 정량적인 평가를 통하여, 원래 영상에 비해 SNR이 최소 5%에서 최대 30%까지 증가하는 것을 확인하였다. 이러한 연구 결과는 향후 dynamic PET 연구의 기초적인 도구로 활용될 것이라 기대된다.

Dynamic positron emission tomography(dPET) is widely used medical imaging modality that can provide both physiological and functional neuro-image for diagnosing various brain disease. However, dPET images have low spatial-resolution and high noise level during spatio-temporal analysis (three-dimensional spatial information + one-dimensional time information), there by limiting clinical utilization. In order to overcome these issues for the spatio-temporal analysis, a novel computational technique was introduced in this paper. The computational technique based on singular value decomposition classifies multiple independent components. Signal components can be distinguished from the classified independent components. The results show that signal to noise ratio was improved up to 30% compared with the original images. We believe that the proposed computational technique in dPET can be useful tool for various clinical / research applications.

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