Synthesis of angiographic images using iterative approximation

In coronary x-ray angiographies, the vessels supplying the heart are imaged in a number of states uniquely determined by a combination of the respiratory intake and the heart contraction of the patient. The angiographic frames of one sequence represent not all possible combinations of respiration and heart contraction. A couple of applications need a continuous and dense sampling of the state-space given by the two axes 'respiration' and 'contraction', e.g. background removal or motion-compensated catheter navigation. We present a novel method of interpolating above the twodimensional phase-space based on pairs of angiographic frames with similar contraction, but different respiration status. First a hypothetical model of the respiration motion is formulated, e.g. rigid transformation or rigid translation. Then the parameters that transform a single frame into another one with similar contraction status are calculated for a number of frames. An iterative approach is used to reconstruct the generalized transformation function from the transformation parameters of frame pairs. Using this function, angiographic frames of arbitrary respiration status can be generated. It is shown that the synthesized angiographies closely match real angiographies acquired at the same combination of contraction and respiration status.

[1]  M. Schrijver,et al.  Angiographic Image Analysis to Assess the Severity of Coronary Stenoses , 2002 .

[2]  T. Aach,et al.  Cardio dynamic subtraction angiography (CDSA) , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[3]  David Atkinson,et al.  A study of the motion and deformation of the heart due to respiration , 2002, IEEE Transactions on Medical Imaging.

[4]  Til Aach,et al.  Statistical-model-based identification of complete vessel-tree frames in coronary angiograms , 2004, IS&T/SPIE Electronic Imaging.

[5]  Til Aach,et al.  Mutual information based respiration detection , 2003, CARS.

[6]  R. Mohan,et al.  Acquiring a four-dimensional computed tomography dataset using an external respiratory signal. , 2003, Physics in medicine and biology.

[7]  Olaf Dössel,et al.  Model evaluation and calibration for prospective respiratory motion correction in coronary MR angiography based on 3-D image registration , 2002, IEEE Transactions on Medical Imaging.

[8]  G. T. Herman,et al.  Computed Masks in Coronary Subtraction Imaging , 1987, IEEE Transactions on Medical Imaging.

[9]  Jörg Bredno,et al.  Algorithmic solutions for live device-to-vessel match , 2004, SPIE Medical Imaging.

[10]  Barbara Martin-Leung,et al.  Software architecture for live enhancement of medical images , 2004, IS&T/SPIE Electronic Imaging.