The goal of this proposed research is to develop a system for determination of imaging geometries for optimal views via computer display of a calculated three-dimensional (3D) coronary vascular tree and for retrospective determination of imaging geometries used in previous studies so that new acquisitions can be made with those geometries while the patient is still on the table. Specifically, we will develop methods (l) to estimate the imaging geometry from biplane angiograms, (2) to determine bifurcation points in biplane angiographic sequences, (3) to determine corresponding points in biplane image sequences, (4) to facilitate determination of optimal views, and (5) to determine retrospectively imaging geometries used in previous studies. Previously, methods have been proposed for determination of the 3D vasculature from biplane images; however, they involve the use of calibration objects or complex measurement protocols, and they are not easily automated. Because the 3D vasculature is not available, multiple acquisitions must be obtained, measurements in coronary images remain subjective and inaccurate, and the imaging geometry of current studies cannot be aligned with that of previous geometries, which reduces the accuracy and precision of comparisons performed in longitudinal studies. In the proposed research, the 3D coronary vasculature will be reconstructed automatically from biplane acquisitions without calibration objects for immediate evaluation. The accuracies in magnification and imaging geometry will be better than 3% and 2 degrees, respectively. With the 3D vasculature, optimal views can be identified without additional radiation dose or contrast load to the patient, and quantitative measurements become more reliable. In addition, we will develop methods for retrospective alignment of current imaging geometries with those of previous studies so that acquisitions with equivalent projections can be obtained to facilitate quantitative measurements of interval change. The significance of the proposed research is that the 3D vasculature will be determined accurately, automatically, and quickly. computerized visualization will allow identification of optimal view, thereby, reducing patient radiation exposure, contrast load, and risk. Immediate retrospective alignment will facilitate longitudinal studies of progression or regression of coronary disease. These techniques can be implemented on current digital biplane systems.
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| Rudin, Stephen; Bednarek, Daniel R; Hoffmann, Kenneth R (2008) Endovascular image-guided interventions (EIGIs). Med Phys 35:301-9 |
| Takemura, Akihiro; Hoffmann, Kenneth R; Suzuki, Masayuki et al. (2008) An algorithm for tracking microcatheters in fluoroscopy. J Digit Imaging 21:99-108 |
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| Singh, Vikas; Mukherjee, Lopamudra; Xu, Jinhui et al. (2007) Brachytherapy seed localization using geometric and linear programming techniques. IEEE Trans Med Imaging 26:1291-304 |
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| Singh, Vikas; Xu, Jinhui; Hoffmann, Kenneth R et al. (2006) Towards a theory of a solution space for the biplane imaging geometry problem. Med Phys 33:3647-65 |
| Dmochowski, Jacek; Hoffmann, Kenneth R; Singh, Vikas et al. (2005) Effects of point configuration on the accuracy in 3D reconstruction from biplane images. Med Phys 32:2862-9 |
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| Subramanian, Navneeth; Kesavadas, T; Hoffmann, Kenneth R (2004) A prototype virtual reality system for preoperative planning of neuro-endovascular interventions. Stud Health Technol Inform 98:376-81 |
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