Particle image velocimetry suitable for X-ray projection imaging
A 2D or 3D velocity field is reconstructed from cross-correlation analysis of image pairs of a sample, without first reconstructing images of the sample spatial structure. The method can be implemented via computer tomographic X-ray particle image velocimetry, using multiple projection angles, with phase contrast images forming dynamic speckle patterns. Estimated cross-correlations may be generated via convolution of a measured autocorrelation function with a velocity probability density function, and the velocity coefficients iteratively optimized to minimize the error between the estimated cross-correlations and the measured cross-correlations. The method may be applied to measure blood flow, and the motion of tissue and organs such as heart and lungs.
1. A method for providing an image of a lung sample having an airway tree, the method comprising the steps of:
a) recording images encoding motion data for the sample in terms of Cartesian coordinates;
b) reconstructing a 2D or 3D motion field from the encoded motion data in the recorded images;
c(i) segmenting an image of the airway tree of the lung sample;
c(ii) associating segments of ends of the airway tree from step c(i) with regions of the 2D or 3D data motion field; and
c(iii) using the regions of the 2D or 3D motion field identified from step c(ii) to determine one or more parameters in one or more other segments of the segmented image;
wherein steps a-c are automated.
2. The method according to claim 1 , wherein the determined one or more parameters are chosen from airflow or tissue compliance.
3. The method according to claim 1 , wherein the motion of human or animal lung tissue is measured.
4. The method according to claim 2 , wherein the motion of air is measured.
5. A computer readable storage medium for storing in non-transient form an application for executing a method of presenting information derived from a lung sample having an airway tree, the method including the steps of:
a) recording images encoding motion data for the lung sample in terms of Cartesian coordinates;
b) reconstructing a 2D or 3D motion field from the motion data encoded in the recorded images;
c(i) segmenting an image of the airway tree of the lung sample;
c(ii) associating segments of ends of the airway tree from step c(i) with regions of the 2D or 3D motion field; and
c(iii) using the regions of the 2D or 3D motion field identified from step c(ii) to determine parameters in one or more other segments of the segmented image;
wherein steps a-c are automated.
6. A system operative on the basis of presenting information derived from a lung sample having an airway tree, the system comprising an image capture means, a computer and a user interface, wherein:
the image capture means records images encoding motion data for the sample in terms of Cartesian coordinates;
the computer reconstructs a 2D or 3D motion field from the motion data encoded in the recorded images;
the computer (i) segments an image of the airway tree of the lung sample, (ii) associates segments of the ends of the airway tree from (i) with regions of the 2D or 3D motion field, and uses the regions of the 2D or 3D motion field identified in (ii) to determine one or more parameters in one or more other segments of the segmented image of (i).