Determination of 3D vessel motion from biplane cardiac sequences

Kenneth R. Hoffmann; Li Lan; Julio Esclarin; Jacqueline Esthappan; Anindya Sen; Kok-Gee Chua

doi:10.1117/12.349603

20 May 1999 Determination of 3D vessel motion from biplane cardiac sequences

Kenneth R. Hoffmann, Li Lan, Julio Esclarin, Jacqueline Esthappan, Anindya Sen, Kok-Gee Chua

Proceedings Volume 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images; (1999) https://doi.org/10.1117/12.349603
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

We have developed methods for determining 3D vessel centerlines from biplane image sequences. For dynamic quantities, e.g., vessel motion or flow, the correspondence between points along calculated centerlines must be established. We have developed and compared two techniques for determination of correspondence and of vessel motion during the heart cycle. Clinical biplane image sequences of coronary vascular trees were acquired. After manual indication of vessel points in each image, vessels were tracked, bifurcation points were calculated, and vascular hierarchy was established automatically. The imaging geometry and the 3D vessel centerlines were calculated for each pair of biplane images from the image data alone. The motion vectors for all centerline points were calculated using corresponding points determined by two methods, either as points of nearest approach of the two centerlines or as having the same cumulative arclength from the vessel origin. Corresponding points calculated using the two methods agreed to within 0.3 cm on average. Calculated motion of vessels appeared to agree with motion visible in the images. Relative 3D positions and motion vectors can be calculated reliably with minimal user interaction.

Citation Download Citation

Kenneth R. Hoffmann, Li Lan, Julio Esclarin, Jacqueline Esthappan, Anindya Sen, and Kok-Gee Chua "Determination of 3D vessel motion from biplane cardiac sequences", Proc. SPIE 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images, (20 May 1999); https://doi.org/10.1117/12.349603

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