Veress, Krisztián

Veress Krisztián

University of Szeged

Parameter Estimation of a Flow-Measurement Function Used inDigital AngiographyKrisztián VeressThe purpose of angiographical procedures [1], [2] used in cardiovascular interventions isto classify the patient’s potential of regeneration after strokes caused by dead blood cells inthe main arteria. The main question of a surgeon is whether the affected cardiac muscle isable to regenerate by allowing blood to flow in and out, or not. The flow of blood into heart’scapillaries is measured using x-ray radiometry with contrastive fluids [3], [4].The intensity of the contrastive fluid flowing into the target cardiac muscle area is deter-mined by means of image processing on angiogramms produced during the radiometry, thusresulting a dataset of positive intensity values. Our task was to estimate the parameters ofa 5-parameter Gamma function — which is well-verified for such problems in this domain— which provides valueable information to the medical team about the patient’s status. Theparameter-estimation of the former function is hard given that the raw dataset is heavily pol-luted with several different noise types.We propose a solution for eliminating the noise by applying a specially designed mov-ing window Gauss filter. We have successfully verified the proposed smoothing algorithmwhich lets us to use the Levenberg-Marquardt local search method on the smoothed dataset.The parameter estimation is done in a nonlinear least-squares way. Our results showed thathigher precision, lower processing times and faster convergence could be achieved using thesmoothed dataset rather than the original one.Moreover, we designed an algorithm for computing an initial guess for the LM algorithmin order to achieve ultimate precision. The method is based on the functional analysis of theGamma model, and statistical computations on the original dataset. Feeding the LM with theprecomputed initial guess, the residuals decreased apace.Finally, a third algorithm is proposed for selecting significant points on the smoothed datasetwith an interval-based classification method. By selecting 10 to 30 significant points from theaverage of 200 data points showed that the parameters of the Gamma model coudl be approx-imated more precisely to the correct values in a biological (not numerical) sense.AcknowledgementsThis work was supported by the Cardiovascular Research Laboratory at the Medical Universityof Szeged.References[1] C.M. Gibson, S. Albert Angiographic Assessment of Both Epicardial and Myocardial Perfusion,Circulation, 109, 3096-3105, (2004)[2] J. Hung-Chi Yu 3D Digital Subtraction Angiography[3] C.M. Gibson, M. Anshelevich, S. Murphy Impact of injections during diagnostic coronary an-giography on coronary patency in the setting of acute myocardial infarction from the TIMI trials,Am J Cardiol., 86, 1378-1379, (2000)[4] C.M. Gibson, A.J. Kirtane, S.A Murphy Impact of contrast agent type (ionic versus non-ionic)used for coronary angiography on angiographic, electrocardiographic and clinical outcomes follow-ing thrombolytic administration in acute MI., Catheter Cardiovasc Interv, 53, 6-11, (2001)78

Parameter estimation of a flow-measurement function used in

digital angiography

http://acta.bibl.u-szeged.hu/59998/1/cscs_2010_078.pdf

Parameter estimation of a flow-measurement function used in digital angiography

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