Image analysis – Applications – Biomedical applications
Reexamination Certificate
2011-05-31
2011-05-31
Lu, Tom Y (Department: 2624)
Image analysis
Applications
Biomedical applications
C382S131000, C382S173000
Reexamination Certificate
active
07953262
ABSTRACT:
A technique for producing a three-dimensional segmented image of blood vessels and automatically labeling the blood vessels. A scanned image of the head is obtained and an algorithm is used to segment the blood vessel image data from the image data of other tissues in the image. An algorithm is used to partition the blood vessel image data into sub-volumes that are then used to designate the root ends and the endpoints of major arteries. An algorithm is used to identify a seed-point voxel in one of the blood vessels within one of the sub-volume of the partition. Other voxels are then coded based on their geodesic distance from the seed-point voxel. An algorithm is used to identify endpoints of the arteries. This algorithm may also be used in the other sub-volumes to locate the starting points and endpoints of other blood vessels. One sub-volume is further sub-divided into left and right, anterior, medial, and posterior zones. Based on their location in one of these zones, the voxels corresponding to the endpoints of the blood vessels are labeled. Starting from these endpoints, the artery segments are tracked back to their starting points using an algorithm that simultaneously labels all of the blood vessel voxels along the path with a corresponding anatomical label identifying the blood vessel to which it belongs.
REFERENCES:
patent: 7177453 (2007-02-01), Suryanarayanan et al.
patent: 7711165 (2010-05-01), Lesage et al.
patent: 2003/0031351 (2003-02-01), Yim
patent: 2005/0110791 (2005-05-01), Krishnamoorthy et al.
patent: 2005/0113679 (2005-05-01), Suryanarayanan et al.
patent: 2006/0120585 (2006-06-01), Zhang et al.
patent: 2008/0146951 (2008-06-01), Zhao et al.
Netherlands Search Report.
Suryanarayanan et al., “Automatic Tracking of Neuro Vascular Tree Paths”, Proc. of SPIE, vol. 6144, pp. 61444N-1 thru 61444N-8, XP-002550700.
Zhang et al., “Automatic Detection of Three-Dimensional Vascular Tree Centerlines and Bifurcations in High-Resolution Magnetic Resonance Angiography”, Investigative Radiology, vol. 40, No. 10, Oct. 2005, pp. 661-671, XP-008113336.
Zhou et al., “Efficient Skeletonization of Volumetric Objects”, IEEE Transactions on Visualization and Computer Graphics, vol. 5, No. 3, pp. 196-209, Jul.-Sep. 1999.
Bulliet et al., “Reconstruction of the Intracerebral Vasculature from MRA and a Pair of Projection Views”, , Medical Image Display and Analysis Group, University of North Carolina, Chapel Hill, Nc, 4 pages, Date: 1997.
Bullitt et al., “Computer-Assisted Measurement of Vessel Shape From 3T Magnetic Resonance Angiography of Mouse Brain”, Methods, vol. 43, pp. 29-34, 2007.
Nowinski et al., The Cerefy Atlas of Cerebral Vasculature (1st edition), Date: 2009.
Kass et al., “Snakes: Active Contour Models”, International Journal of Computer Vision, pp. 321-331, 1988.
Takemura et al., “Automatic Segmentation Method Which Divides a Cerebral Artery Tree in Time-Of-Flight MR-Angiography Into Artery Segments”, Proc. of SPIE, vol. 6144, pp. 61443G-1 to 61443G-9, 2006.
Bullitt et al., “Measuring Tortuosity of the Intracerebral Vasculature From MRA Images”, IEEE Transactions on Medical Imaging, vol. 22, No. 9, pp. 1163-1171, Sep. 2003.
Sato et al., “Three-Dimensional Multi-Scale Line Filter for Segmentation and Visualization of Curvilinear Structures in Medical Images”, Medical Image Analysis, vol. 2, No. 2, pp. 143-168, 1998.
Villablanca et al., “Detection and Characterization of Very Small Cerebral Aneurysms By Using 2D and 3D Helical CT Angiography”, AJNR Am J Neuroradiol, vol. 23, pp. 1187-1198, Aug. 2002.
Saha et al., “Automatic Bone-Free Rendering of Cerebral Aneurysms via 3D-CTA”, Medical Imaging 2001: Image Processing, Proc. SPIE, vol. 4322, pp. 1264-1272, 2001.
Suryanarayanan et al., “Automatic Tracking of Neuro Vascular Tree Paths”, Medical Imaging 2006: Image Processing, Proc. SPIE, vol. 6144, pp. 61444N-1 to 61444N-8, 2006.
Gopinath Ajay
Joshi Mukta C.
Mallya Yogisha
Shriram Krishna Seetharam
Suryanarayanan Srikanth
Asmus Scott J.
General Electric Company
Lu Tom Y
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