Conventional vessel tracking and segmentation techniques identify the positions and two- dimensional structure of arteries in each frame of the angiographic sequence, but cannot distinguish the artery and background contributions to the intensity. We report a new technique for motion-compensated estimation of artery and background structures in coronary angiograms. The image within a region of interest is modeled as consisting of a sum of two independently moving layers, one of which contains the artery and one consisting of only background structures. The density of each of these layers is solved under two assumptions: (1) within each layer, the density varies from frame to frame only by rigid translation, and (2) the sum of the densities of the two layers equals the actual image density. This technique can be used to enhance image sequences by subtracting the component of the background whose temporal variation is entirely due to rigid translation. The feasibility of this technique is demonstrated on synthetic and clinical image sequences.
[1]
Sergei Fogel,et al.
The estimation of velocity vector fields from time-varying image sequences
,
1991,
CVGIP Image Underst..
[2]
Shinichi Tamura,et al.
Estimation of motion from sequential images using integral constraints
,
1995,
Pattern Recognit..
[3]
Jack Sklansky,et al.
Flexible mask subtraction for digital angiography
,
1992,
IEEE Trans. Medical Imaging.
[4]
S T Rake.
Three-dimensional reconstruction of arteries from biplane angiograms.
,
1991,
Medical informatics = Medecine et informatique.
[5]
Shinichi Tamura,et al.
Automated motion estimation from M-mode echocardiograms
,
1994,
Optics & Photonics.