A New Method of Estimating Coronary Artery Diameter Using Direction Codes

방향코드를 이용한 관상동맥의 직경 측정 방법

  • 전춘기 (생산기술연구원 산업기술교육센터 메카트로닉스과) ;
  • 강광남 (생산기술연구원 산업기술교육센터 메카트로닉스과) ;
  • 이태원 (생산기술연구원 산업기술교육센터 메카트로닉스과)
  • Published : 1995.09.01

Abstract

The conventionally used method requires centerline of vessels to estimate the vessel diameter. Two methods of estimating the centerline of vessels are reported : One is manually observer-defined method. This potentially contributes to inter-and intra-observer variability. And the other is to auto- matically detect the centerline of vessels. But this is very complicated method. In this paper, we propose a new method of estimating vessel diameter using direction codes and position informs:ion without detecting centerline. Since this method detects the vessel boundary and direction code at d same time, it simplifies the procedure and reduces execution time in estimating the vessel diameter. Compared to a method that automatically estimates the vessel diAmeter uslng centerline, our method provides improved accuracy in image with poor contrast, branching or obstructed vessels. Also, this provides a good compression of boundary description, because each direction code element can be coded with 3 bits only, instead of the 4 bytes required for the storage of the coordinates of each border pixel. Our experiments demonstrate the usefulness of the technique using direction code for quantitative analysis of coronary angiography Experimental results Justify the validity of the proposed method.

지금까지는 혈관의 중심선을 구해서 혈관의 직경을 측정해 왔다. 혈관의 중심선을 구하는 방법은 2가지가 보고되어 있는데 그중 하나는 maunal로 중심선을 찾는 observer-defined 방법이다. 이 방법을 사용자에 따라 변화할 가능성이 잠재한다, 또 다른 방법은 자동으로 혈관의 중심을 찾아내는 것인데 대단히 복잡하다. 이 논문에서, 중심선을 찾지 않고 방향코드와 위치정보를 이용하여 직경을 구하는 새로운 방법을 제안한다. 이 방법은 경계선과 방향코드를 동시에 검출하기 때문에 절차가 간단해지고 처리속도도 빨라진다. 중앙선을 이용하여 자동으로 혈관직경을 구하는 방법과 비교해보면, 가지가 있거나 장애가 있는 혈관 이미지에 있어서 정확도가 개선된다. 또한 방향 코드는 3비트로 코드화되기 때문에 혈관정보를 압축 저장하는데 용이하다. 이 방법은 실험을 통하여 유용성이 있음을 확인하였다.

Keywords

References

  1. circulation v.55 Variability in the analysis of coronary arteriograms T.A.De Rouen;J.A.Murray;T.Takaro
  2. IEEE Trans. Med. Imaging v.MI-8 Automated analysis of coronary arterial morphology in cineangiograms : Geometric and physiologic validation in humans S.R.Fleage;M.R.Johnson;C.J.Wilbricht;D.J.Skorton;R.F.Wilson;C.W.White;M.L.Marcus;S.M.Collins
  3. Cardiac Imaging and Image Processing STEVE M.COLLINS;DAVID J.SKORTON
  4. circulation v.68 Computerized image analysis for quantitative measurement of vessel diameter from cineangiograms J.R.Spears;D.P.Sandor;A.Als;M.Malagold;J.E.Markis;W.Grossman;J.R.Serur;S.Paulin
  5. computers in cardiology, Long Beach, CA, IEEE Computer society Automated evaluation of vessel diameter from arterigrams R.L.Kirkeeide;P.Fung;R.W.Smalling;K.L.Gould
  6. IEEE Trans. Med. Imaging v.MI-6 High precision quantitative angiography T.Sandor;A.D'Adamo;W.B.Hanlon;J.R.Spears
  7. Philips Medical Systems, operator's manual INTEGRIS H3000 Release 1
  8. Circulation v.75 Automated quantitative coronary arteriography : morphologic and physiologic validation in vivo of a rapid digital angiographic method G.B.J.Mancini;S.B.Simon;M.J.Mcgillem;M.T.Lefree;H.Z.Friedman;R.A.Vogel
  9. Invest. Radiol. v.23 Videoensitometric analysis of coronary stenoses : in vivo geometric and physiologic validation in humans M.R.Johnson;D.J.Skorton;E.E.Ericksen;S.R.Fleagle;R.F.Wilson;L.F.Hiratzka;C.W.White;M.L.Marcus;S.M.Collins
  10. Circulation v.73 Changes in coronary lumen cross-sectional area in the six months after angioplasty : A quantitative analysis of the variable response to percutaneous transluminal angioplasty M.R.Johnson;E.E.Ericksen;S.M.Collins;D.J.Skorton;D.G.Harrison;M.L.Marcus;C.W.White
  11. Amer. Heart J. v.116 Assessment of coronary angioplasty by an automated digital angiographic method D.Katritsis;D.A.Lythall;M.H.Anderson;I.C.Cooper;M.M.Webb-Peploe
  12. Circulation v.55 Quantitative coronary arterigraphy;Estimation of dimensions, hemodynamic resistance, and atheroma mass of coronary artery lesions using the arterigram and digital computation B.G.Brown;E.Bolson;M.Frimer;H.Dodge
  13. Proc. SPIE v.626 Digital radiographic assessment of coronary arterial geometric diameter and videodensitometric cross-sectional area M.T.LeFree;S.B.Simon;G.B.J.Mancini;R.A.Vogel
  14. Two dimensional Signal and Image Processing JAE S.LIM
  15. IEEE Trans. Med. Imaging v.12 Simultaneous Detection of both Coronary Borders Milan Sonka;Christopher J.Willbricht;Steven R.Fleagle;Satish K.Tadikonda;Michael D.Winniford;Steve M.Collins
  16. J. Am. Coll. Cardiol. v.15 Relative insensitivity of densitometric stenosis measurement to lumen edge detection E.M.Herrold;H.L.Goldberg;J.S.Borer;K.Wong;J.W.Moses