IMAGE DATA PROCESSING SYSTEMS
First Claim
1. A method of determining data defining an estimate of the thickness of a tissue structure from tomographic imaging data, the method comprising:
- inputting a tomographic imaging data set defining at least one slice through a region of tissue including said tissue structure;
modelling said tissue structure as a variation of an imaging parameter of said imaging data along a line crossing said tissue structure, a tissue structure model defined by said variation having at least a first tissue modelling parameter defining a value of said imaging parameter along said line and within said tissue structure and having at least one parameter defining said thickness of said tissue structure;
modelling a variation of said tomographic imaging data along said line as a blurred version of said variation of said imaging parameter modelling said tissue structure to provide a blurred tomographic imaging model, said blurred version of said variation of said imaging parameter being defined by a blurring function applied to said tissue structure model, wherein said blurred tomographic imaging model has a blurring parameter representing a degree of blurring applied by said blurring function;
determining a constraining value of said first tissue modelling parameter; and
fitting said blurred tomographic imaging model defining said blurred version of said variation of said imaging parameter along said line, to data derived from said tomographic imaging data set;
wherein said fitting comprises holding said first tissue modelling parameter substantially at said constraining value and allowing variation of said blurring parameter and said at least one parameter defining said thickness of said tissue structure to determine said at least one parameter defining said thickness of said tissue structure; and
wherein said at least one parameter defining said thickness of said tissue structure comprises said data defining said estimate of said thickness of said tissue structure.
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Abstract
We describe a method of estimating the thickness of a tissue structure, in particular cortical bone thickness from tomographic imaging data such as CT data. The method models the tissue structure as a variation of an imaging parameter along a line; models a variation of the tomographic imaging data along the line as a blurred version of the variation of the imaging parameter modelling the; and fits the blurred tomographic imaging model to data from the tomographic imaging by holding a tissue modelling parameter at a constraining value and allowing variation of a blurring parameter and at least one parameter defining the thickness of the tissue structure to determine an estimate of the thickness of the structure.
17 Citations
21 Claims
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1. A method of determining data defining an estimate of the thickness of a tissue structure from tomographic imaging data, the method comprising:
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inputting a tomographic imaging data set defining at least one slice through a region of tissue including said tissue structure; modelling said tissue structure as a variation of an imaging parameter of said imaging data along a line crossing said tissue structure, a tissue structure model defined by said variation having at least a first tissue modelling parameter defining a value of said imaging parameter along said line and within said tissue structure and having at least one parameter defining said thickness of said tissue structure; modelling a variation of said tomographic imaging data along said line as a blurred version of said variation of said imaging parameter modelling said tissue structure to provide a blurred tomographic imaging model, said blurred version of said variation of said imaging parameter being defined by a blurring function applied to said tissue structure model, wherein said blurred tomographic imaging model has a blurring parameter representing a degree of blurring applied by said blurring function; determining a constraining value of said first tissue modelling parameter; and fitting said blurred tomographic imaging model defining said blurred version of said variation of said imaging parameter along said line, to data derived from said tomographic imaging data set; wherein said fitting comprises holding said first tissue modelling parameter substantially at said constraining value and allowing variation of said blurring parameter and said at least one parameter defining said thickness of said tissue structure to determine said at least one parameter defining said thickness of said tissue structure; and wherein said at least one parameter defining said thickness of said tissue structure comprises said data defining said estimate of said thickness of said tissue structure. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. Tissue structure thickness estimation apparatus for determining data defining an estimate of the thickness of a tissue structure from tomographic imaging data, the apparatus comprising:
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an input for inputting a tomographic imaging data set defining at least one slice through a region of tissue including said tissue structure; working memory for storing data; program memory storing processor control code; and a processor coupled to said input, to said working memory, and to said program memory; and wherein said stored processor control code comprises code to; model said tissue structure as a variation of an imaging parameter of said imaging data along a line crossing said tissue structure, a tissue structure model defined by said variation having at least a first tissue modelling parameter defining a value of said imaging parameter along said line and within said tissue structure and having at least one parameter defining said thickness of said tissue structure; model a variation of said tomographic imaging data along said line as a blurred version of said variation of said imaging parameter modelling said tissue structure to provide a blurred tomographic imaging model, said blurred version of said variation of said imaging parameter being defined by a blurring function applied to said tissue structure model, wherein said blurred tomographic imaging model has a blurring parameter representing a degree of blurring applied by said blurring function; determine a constraining value of said first tissue modelling parameter; and said blurred tomographic imaging model defining said blurred version of said variation of said imaging parameter along said line, to data derived from said tomographic imaging data set; wherein said fitting comprises holding said first tissue modelling parameter substantially at said constraining value and allowing variation of said blurring parameter and said at least one parameter defining said thickness of said tissue structure to determine said at least one parameter defining said thickness of said tissue structure; and wherein said at least one parameter defining said thickness of said tissue structure comprises said data defining said estimate of said thickness of said tissue structure.
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13. A method of estimating the position of an edge of or the thickness of cortical bone from CT data, the method comprising:
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modelling a CT image of said cortical bone using a piecewise constant bone density model blurred by a CT imaging blurring function; fitting said CT data to said modelled blurred CT image by allowing said blurring function to vary whilst constraining a value of cortical bone density represented by said bone density model to be substantially fixed; and estimating said position of said edge or said thickness of said cortical bone from a parameter of said fitted model. - View Dependent Claims (14, 15, 16, 17)
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18. Apparatus for estimating the position of an edge of or the thickness of cortical bone from CT data, the apparatus comprising:
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working memory for storing data; program memory storing processor control code; and a processor coupled to said input, to said working memory, and to said program memory; and wherein said stored processor control code comprises code to; model a CT image of said cortical bone using a piecewise constant bone density model blurred by a CT imaging blurring function; fit said CT data to said modelled blurred CT image by allowing said blurring function to vary whilst constraining a value of cortical bone density represented by said bone density model to be substantially fixed; and estimate said position of said edge or said thickness of said cortical bone from a parameter of said fitted model.
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19. A method of providing a representation of cortical bone thickness from CT data, the method comprising:
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inputting CT image data of said cortical bone; generating a 2-D or 3-D needle map of an outer perimeter or surface of said cortical bone, said needle map defining a plurality of perimeter normals or surface normals to said cortical bone at a plurality of respective portions on said outer perimeter or surface; determining a thickness estimate of said cortical bone at each of said positions along a direction of a respective said perimeter normal or surface normal for the position; and generating mapping data representing a 2-D or 3-D map defining said estimated cortical thickness at each of said plurality of positions overlaid on a respective 2-D representation of said perimeter or 3-D representation of said surface of said cortical bone. - View Dependent Claims (20)
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21. Apparatus for providing a representation of cortical bone thickness from CT data, the apparatus comprising:
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working memory for storing data; program memory storing processor control code; and a processor coupled to said input, to said working memory, and to said program memory; and wherein said stored processor control code comprises code to; input CT image data of said cortical bone; generate a 2-D or 3-D needle map of an outer perimeter or surface of said cortical bone, said needle map defining a plurality of perimeter normals or surface normals to said cortical bone at a plurality of respective portions on said outer perimeter or surface; determine a thickness estimate of said cortical bone at each of said positions along a direction of a respective said perimeter normal or surface normal for the position; and generate mapping data representing a 2-D or 3-D map defining said estimated cortical thickness at each of said plurality of position overlaid on a respective 2-D representation of said perimeter or 3-D representation of said surface of said cortical bone.
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Specification