Vessel centerline determination
First Claim
1. A method of centerline determination for a tubular tissue in a digital medical image data set defined in a digital data space, comprising:
- receiving coordinates of at least one start point and one end point inside a tubular tissue volume of the digital data space;
automatically determining a path between said points that remains inside said volume, comprising using targeted marching which uses a cost function incorporating both path cost and estimated future path cost;
automatically segmenting said tubular tissue using said path; and
automatically determining a centerline for said tubular tissue from said segmentation,wherein said receiving, said determining a path, said segmenting, and said determining a centerline are all performed on a same digital data space of said digital medical image data set.
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Abstract
A method of centerline determination for a tubular tissue in a medical image data set defined in a data space, comprising receiving at least one start point and one end point inside a tubular tissue volume; automatically determining a path between said points that remains inside said volume; automatically segmenting said tubular tissue using said path; and automatically determining a centerline for said tubular tissue from said segmentation, wherein said receiving, said determining a path and said segmenting, said determining a centerline are all performed on a same data space of said medical image data set.
29 Citations
69 Claims
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1. A method of centerline determination for a tubular tissue in a digital medical image data set defined in a digital data space, comprising:
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receiving coordinates of at least one start point and one end point inside a tubular tissue volume of the digital data space; automatically determining a path between said points that remains inside said volume, comprising using targeted marching which uses a cost function incorporating both path cost and estimated future path cost; automatically segmenting said tubular tissue using said path; and automatically determining a centerline for said tubular tissue from said segmentation, wherein said receiving, said determining a path, said segmenting, and said determining a centerline are all performed on a same digital data space of said digital medical image data set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68)
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69. A method of centerline determination for a tubular tissue in a digital medical image data set defined in a digital data space, comprising:
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receiving at least one start point and one end point inside a tubular tissue volume; automatically determining a path between said points that remains inside said volume, comprising determining using targeted marching which uses a cost function incorporating both path cost and estimated future path cost, wherein a path cost of a point is a function of a probability of the point being inside or outside of the tubular tissue; automatically segmenting said tubular tissue using said path; and automatically determining a centerline for said tubular tissue from said segmentation, wherein said receiving, said determining a path, said segmenting, and said determining a centerline are all performed on a same digital data space of said digital medical image data set.
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Specification