Functional X-ray Neuro Image Analysis

Functional X-ray Neuro Image Analysis


Sven Lončarić

Draženko Babić

Hrvoje Bogunović

Robert Homan


University of Zagreb, Faculty of Electrical Engineering and Computing (

Philips Healthcare, Best, The Netherlands (

Project duration



Philips Healthcare, Best, The Netherlands (


Quantitative functional measurements can significantly improve diagnostic value of x-ray angiograms. Of several different functional parameters three have clinical importance: blood flow velocity, perfusion and diffusion. X-ray imaging can provide only first two parameters, of which perfusion imaging is more important due to several important hemodynamic parameters: cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT).

The primary aim of this project was to exploit good characteristics of x-ray imaging and develop functional analysis techniques that will help in studying of the human physiologic characteristics associated with known pathologies.


The basic measurement from which all parameters are extracted is the time-density signal obtained from a sequence of DSA images. Blood flow and velocity estimation in arteries is supported with the 3D volume of the vessel tree obtained before the DSA images and registered to the DSA dataset. Blood flow is of interest in two distinct regions, the arteries and the capillary region. Arterial blood flow measurement is based on blood velocity and vessel cross-section area estimation. Blood velocity is obtained by measuring the transit time of the contrast agent through the vessel of known length. Transit time is obtained by measuring the time of arrival of contrast agent to different parts of the projected vessels. Blood flow at the capillary level is called perfusion and measurement is based on the theory of perfusion MRI and CT modalities. The time activity signal of each region is obtained and its characteristics are linked to physiological parameters of interest using maximum slope model.


Hrvoje Bogunović, Blood Flow Analysis From Angiogram Image Sequence, Master Thesis, Zagreb, 2005

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