The University of North Carolina at Chapel Hill

Stephen Aylward

Elizabeth Bullitt

Stephen Murray Pizer

Daniel Scott Fritsch

Julien Jomier

Methods, systems, and computer program products for hierarchical registration () between a blood vessel and tissue surface model () for a subject and a blood vessel and tissue surface image for the subject are disclosed. According to one method, hierarchical registration of a vascular model to a vascular image is provided. According to the method, a vascular model is mapped to a target image using a global rigid transformation to produce a global-rigid-transformed model. Piecewise rigid transformations are applied in a hierarchical manner to each vessel tree in the global-rigid-transformed model to perform a piecewise-rigid-transformed model. Piecewise deformable transformations are applied to branches in the vascular tree in the piecewise-transformed-model to produce a piecewise-deformable-transformed model.

Methods, systems, and computer program products for hierarchical registration between a blood vessel and tissue surface model for a subject and a blood vessel and tissue surface image for the subject

Systems, methods, and computer program products for analysis of vessel attributes for diagnosis, disease staging, and surgical planning are disclosed. A method for analyzing blood vessel attributes may include developing an atlas including statistical measures for at least one blood vessel attribute. The statistical measures can be developed from blood vessel image data from different individuals. Blood vessel attribute measurements can be obtained from an individual subject. The individual subject's blood vessel attribute measurements can be compared to the statistical measures in the atlas. Output may be produced indicative of a physical characteristic of the individual based on results from the comparison.

Systems, methods, and computer program products for analysis of vessel attributes for diagnosis, disease staging, and surgical planning

Systems and methods are disclosed for processing tubular objects in multi-dimensional images. The processing includes generating representations of tubular objects which enable subsequent analysis. Systems and methods for processing tubular objects in a multi-dimensional image include establishing a seed points in a multi-dimensional image, searching for an extremum point corresponding to a tubular object having a central curve of intensity extrema, and extracting a one-dimensional central track corresponding to the tubular object and extents corresponding to a plurality of cross-sections along the tubular object. A number of embodiments are presented which apply the systems and methods to a variety of imaging applications.

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Carrboro, NC, United States of America

Stephen Aylward