Method for segmenting anatomical structures from 3D image data by using topological information
First Claim
1. A method for segmenting anatomical structures from 3D image data, the method comprising:
- setting a starting point in the 3D image data;
identifying at least one of at least one known anatomically significant point and at least one known anatomically significant surface in the 3D image data;
segmenting, proceeding from the starting point, the anatomical structure pixel by pixel with a multiplicity of segmentation steps such that an instantaneous distance is determined automatically relative to at least one of the at least one known anatomically significant point and to the at least one known anatomically significant surface in each segmentation step;
establishing at least one of segmentation parameters and a selection of adjacent pixels for continuing the segmentation as a function of the determined distance, taking account of a model topology; and
displaying a result of the segmentation process,wherein when a truncation point during the segmentation process is reached at a position at which the anatomical structure should not be truncated, based on the model topology, a search algorithm searches for pixels and continues the segmentation of the anatomical structure in an image region determined by an extrapolation of the already segmented anatomical structure, andwherein a gap in the segmented anatomical structure is filled up by means of interpolation.
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Abstract
A method is disclosed for segmenting anatomical structures, in particular the coronary vessel tree, from 3D image data. In the method, a starting point is initially set in the 3D image data, and at least one known anatomically significant point and/or at least one known anatomically significant surface are/is identified in the 3D image data. Subsequently, proceeding from the starting point the structure is subsequently segmented pixel by pixel with the aid of a multiplicity of segmentation steps in such a way that an instantaneous distance is determined automatically relative to the anatomically significant point and/or to the anatomically significant surface in each segmentation step. Further, segmentation parameters and/or a selection of adjacent pixels for continuing the segmentation are/is established as a function of the distance, taking account of a model topology. The method enables an accurate and reliable segmentation of the anatomical structure.
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Citations
18 Claims
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1. A method for segmenting anatomical structures from 3D image data, the method comprising:
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setting a starting point in the 3D image data; identifying at least one of at least one known anatomically significant point and at least one known anatomically significant surface in the 3D image data; segmenting, proceeding from the starting point, the anatomical structure pixel by pixel with a multiplicity of segmentation steps such that an instantaneous distance is determined automatically relative to at least one of the at least one known anatomically significant point and to the at least one known anatomically significant surface in each segmentation step; establishing at least one of segmentation parameters and a selection of adjacent pixels for continuing the segmentation as a function of the determined distance, taking account of a model topology; and displaying a result of the segmentation process, wherein when a truncation point during the segmentation process is reached at a position at which the anatomical structure should not be truncated, based on the model topology, a search algorithm searches for pixels and continues the segmentation of the anatomical structure in an image region determined by an extrapolation of the already segmented anatomical structure, and wherein a gap in the segmented anatomical structure is filled up by means of interpolation. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 14, 15, 16, 17)
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10. A method for segmenting anatomical structures from a starting point in 3D image data, the method comprising:
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identifying at least one of at least one known anatomically significant point and at least one known anatomically significant surface in the 3D image data; determining a distance relative to at least one of the at least one known anatomically significant point and to the at least one known anatomically significant surface in each of a plurality of segmentations, the plurality of segmentations proceeding pixel by pixel from the starting point; establishing at least one of segmentation parameters and a selection of adjacent pixels for continuing the segmentation process, at least partially as a function of the determined distance; and displaying a result of the segmentation process, wherein when a truncation point during the segmentation process is reached at a position at which the anatomical structure should not be truncated, based on a model topology, a search algorithm searches for pixels and continues the segmentation of the anatomical structure in an image region determined by an extrapolation of the already segmented anatomical structure, and wherein a gap in the segmented anatomical structure is filled up by means of interpolation. - View Dependent Claims (11, 12, 13, 18)
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Specification