Method and system for the computerized analysis of bone mass and structure

Abstract

An automated method, storage medium, and system for analyzing bone. Digital image data corresponding to an image of the bone are obtained. Next there is determined, based on the digital images, a measure of bone mineral density (BMD) and at least one of a measure of bone geometry, a Minkowski dimension, and a trabecular orientation. The strength of the bone is estimated based upon the measure of BMD and at least one of the measure of bone geometery, the Minkowski dimension, and the trabecular orientation. To improve bone texture analysis, the present invention also provides a novel automated method, storage medium, and system in which digital image data corresponding to an image of the bone is obtained, and a region of interest (ROI) is selected within the bone. A fractal characteristic of the image data within the ROI using an artificial neural network is extracted. The strength of the bone is estimated based at least in part on the extracted fractal characteristic. To perform bone analysis with an improved measure of bone mineral density, the present invention also provides a novel automated method, storage medium, and system in which digital image data corresponding to an image of the bone is obtained. A measure of normalized bone mineral density (BMD) corresponding to a volumetric bone mineral density of the bone is determined, and the strength of the bone based is estimated based at least in part on the normalized BMD.

What is claimed as new and desired to be secured by Letters Patent of the United States is:  
     
         1 . A method for the analysis of bone, comprising: 
 obtaining digital image data corresponding to an image of the bone;    determining, based on said digital image data, at least one of a measure of bone geometry, a Minkowski dimension, and a trabecular orientation;    estimating the strength of the bone based upon the at least one of the measure of bone geometry, the Minkowski dimension, and the trabecular orientation.    
     
     
         2 . The method of  claim 1 , wherein: 
 said determining step comprises determining bone mineral density (BMD); and    said estimating step comprises estimating the strength of the bone based at least in part upon the determined BMD.    
     
     
         3 . The method of  claim 1 , further comprising: 
 inputting subject data; and    wherein said estimating step comprises estimating the strength of the bone based at least in part upon on the input subject data.    
     
     
         4 . The method of  claim 3 , wherein said inputting step comprises: 
 inputting the age of the patient whose bone is being analyzed as said subject data.    
     
     
         5 . The method of  claim 1 , further comprising: 
 determining both of the Minkowski dimension for the bone and the trabecular orientation of the bone;    inputting subject data of the patient whose bone is being analyzed; and    the step of estimating comprising estimating bone strength based on the measure of the Minkowski dimension, the trabecular orientation, and the subject data.    
     
     
         6 . The method of  claim 5 , wherein: 
 said determining step comprises determining bone mineral density (BMD): and    said estimating step comprises estimating the strength of the bone based at least in part upon on the determined BMD.    
     
     
         7 . The method of  claim 1 , further comprising: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         8 . The method of  claim 6 , further comprising: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         9 . The method of  claim 2 , wherein the step of determining the BMD comprises: 
 determining an area-based BMD as the measure of BMD.    
     
     
         10 . The method of  claim 2 , wherein: 
 the determining step comprises determining a normalized BMD corresponding to a voltumetric bone mineral density of the bone as the measure of BMD; and    the estimating step comprises estimating the strength of the bone based at least in part on the normalized BMD.    
     
     
         11 . The method of  claim 10 , wherein the step of determining the normalized BMD comprises: 
 determining an area-based BMD of the bone;    performing bone geometry analysis to generate a measure of bone geometry; and    determining the normalized BMD from the area-based BMD and the measure of bone geometry.    
     
     
         12 . The method of  claim 11 , wherein the step of performing bone geometry analysis comprises: 
 determining a neck width of the bone.    
     
     
         13 . The method of  claim 11 , wherein the step of performing bone geometry analysis comprises: 
 determining a shaft width of the bone.    
     
     
         14 . The method of  claim 1 , further comprising: 
 selecting a region of interest (ROI) within the bone;    performing texture analysis of the image data within the ROI to determine at least one measure of bone structure; and    the estimating step comprising estimating the strength of the bone based at least in part on the at least one measure of bone structure.    
     
     
         15 . The method of  claim 14 , wherein the step of performing texture analysis comprises: 
 extracting fractal characteristics of the image data within the ROI using an artificial neural network, said at least one measure of bone structure including the fractal characteristics.    
     
     
         16 . The method of  claim 14 , wherein the step of performing texture analysis comprises: 
 determining a directional Minkowsi dimension for the image data within the ROI, said at least one measure of bone structure including the directional Minkowski dimension.    
     
     
         17 . The method of  claim 14 , wherein the step of performing texture analysis comprises: 
 determining a trabecular orientation for the image data within the ROI, said at least one measure of bone structure including the trabecular orientation.    
     
     
         18 . The method of  claim 10 , further comprising: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         19 . A method for the analysis of bone, comprising: 
 obtaining digital image data corresponding to an image of the bone;    selecting a region of interest (ROI) within the bone;    extracting a fractal characteristic of the image data within the ROI using an artificial neural network; and    estimating the strength of the bone based at least in part on the extracted fractal characteristic.    
     
     
         20 . The method of  claim 19 , wherein said extracting step comprises: 
 performing fractal analysis of the image data within the ROI to generate slope data; and    inputting the slope data into the artificial neural network to generate information representative of bone strength.    
     
     
         21 . A method for the analysis of bone, comprising: 
 obtaining digital image data corresponding to an image of the bone;    determining a measure of normalized bone mineral density (BMD) corresponding to a volumetric bone mineral density of the bone; and    estimating the strength of the bone based based at least in part on the normalized BMD.    
     
     
         22 . The method of  claim 21 , wherein the step of determining the normalized BMD comprises: 
 determining an area-based BMD of the bone;    performing bone geometry analysis to generate a measure of bone geometry; and    determining the normalized BMD from the area-based BMD and the measure of bone geometry.    
     
     
         23 . The method of  claim 22 , further comprising: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         24 . A computer readable medium storing computer instructions for the analysis of bone, by performing the steps of: 
 obtaining digital image data corresponding to an image of the bone;    determining, based on said digital image data, at least one of a measure of bone geometry, a Minkowski dimension, and a trabecular orientation;    estimating the strength of the bone based upon the at least one of the measure of bone geometry, the Minkowski dimension, and the trabecular orientation.    
     
     
         25 . The computer readable medium of  claim 24 , wherein: 
 said determining step comprises determining bone mineral density (BMD); and    said estimating step comprises estimating the strength of the bone based at least in part upon on the determined BMD.    
     
     
         26 . The computer readable medium of  claim 24 , further storing instructions for performing the steps of: 
 inputting subject data; and    wherein said estimating step comprises estimating the strength of the bone based at least in part upon on the input subject data.    
     
     
         27 . The computer readable medium of  claim 26 , wherein said inputting step comprises: 
 inputting the age of the patient whose bone is being analyzed as said subject data.    
     
     
         28 . The computer readable medium of  claim 24 , further storing instructions for performing the steps of: 
 determining both of the Minkowski dimension for the bone and the trabecular orientation of the bone;    inputting subject data of the patient whose bone is being analyzed; and    the step of estimating comprising estimating bone strength based on the measure of the Minkowski dimension, the trabecular orientation, and the subject data.    
     
     
         29 . The computer readable medium of  claim 28 , wherein said determining step comprises determining BMD and said estimating step comprises estimating the strength of the bone based at least in part upon on the determined BMD.  
     
     
         30 . The computer readable medium of  claim 24 , further storing instructions for performing the steps of: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         31 . The computer readable medium of  claim 29 , further storing instructions for performing the steps of: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         32 . The computer readable medium of  claim 25 , wherein the step of determining the BMD comprises: 
 determining an area-based BMD as the measure of BMD.    
     
     
         33 . The computer readable medium of  claim 25 , wherein: 
 the determining step comprises determining a normalized BMD corresponding to a volumetric bone mineral density of the bone as the measure of BMD; and    the estimating step comprises estimating the strength of the bone based at least in part on the normalized BMD.    
     
     
         34 . The computer readable medium of  claim 33 , wherein the step of determining the normalized BMD comprises: 
 determining an area-based BMD of the bone;    performing bone geometry analysis to generate a measure of bone geometry; and    determining the normalized BMD from the area-based BMD and the measure of bone geometry.    
     
     
         35 . The computer readable medium of  claim 34 , wherein the step of performing bone geometry analysis comprises: 
 determining a neck width of the bone.    
     
     
         36 . The computer readable medium of  claim 34 , wherein the step of performing bone geometry analysis comprises: 
 determining a shaft width of the bone.    
     
     
         37 . The computer readable medium of  claim 24 , further storing instructions for performing the steps comprising: 
 selecting a region of interest (ROI) within the bone;    performing texture analysis of the image data within the ROI to determine at least one measure of bone structure; and    the step of estimating comprising estimating the strength of the bone based at least in part on the at least one measure of bone structure.    
     
     
         38 . The computer readable medium of  claim 37 , wherein the step of performing texture analysis comprises: 
 extracting fractal characteristics of the image data within the ROI using an artificial neural network, said at least one measure of bone structure including the fractal characteristics.    
     
     
         39 . The computer readable medium of  claim 37 , wherein the step of performing texture analysis comprises: 
 determining a directional Minkowsi dimension for the image data within the ROI, said at least one measure of bone structure including the directional Minkowski dimension.    
     
     
         40 . The computer readable medium of  claim 37 , wherein the step of performing texture analysis comprises: 
 determining a trabecular orientation for the image data within the ROI, said at least one measure of bone structure including the trabecular orientation.    
     
     
         41 . The computer readable medium of  claim 33 , further storing instructions for performing the steps comprising: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         42 . A computer readable medium storing computer instructions for the analysis of bone, by performing the steps of: 
 obtaining digital image data corresponding to an image of the bone;    selecting a region of interest (ROI) within the bone;    extracting a fractal characteristic of the image data within the ROI using an artificial neural network; and    estimating the strength of the bone based at least in part on the extracted fractal characteristic.    
     
     
         43 . A computer readable medium according to  claim 42 , wherein said extracting step comprises: 
 performing fractal analysis of the image data within the ROI to generate slope data; and    inputting the slope data into the artificial neural network to generate information representative of bone strength.    
     
     
         44 . A computer readable medium storing computer instructions for the analysis of bone, by performing the steps of: 
 obtaining digital image data corresponding to an image of the bone;    determining a measure of normalized bone mineral density (BMD) corresponding to a volumetric bone mineral density of the bone; and    estimating the strength of the bone based based at least in part on the normalized BMD.    
     
     
         45 . A computer readable medium according to  claim 44 , wherein the step of determining the normalized BMD comprises: 
 determining an area-based BMD of the bone;    performing bone geometry analysis to generate a measure of bone geometry; and    determining the normalized BMD from the area-based BMD and the measure of bone geometry.    
     
     
         46 . A computer readable medium according to  claim 45 , further comprising: 
 predicting the likelihood of bone fracture from the estimation of bone strength.    
     
     
         47 . A system for the analysis of bone, comprising: 
 a mechanism configured to obtain digital image data corresponding to an image of the bone;    a mechanism configured to determine, based on said digital image data, at least one of a measure of bone geometry, a Minkowski dimension, and a trabecular orientation;    a mechanism configured to estimate the strength of the bone based upon the at least one of the measure of bone geometry, the Minkowski dimension, and the trabecular orientation.    
     
     
         48 . The system of  claim 47 , wherein: 
 said determining mechanism comprises a mechanism configured to determine bone mineral density (BMD); and    said estimating mechanism comprises a mechanism configured to estimate the strength of the bone based at least in part upon on the determined BMD.    
     
     
         49 . The system of  claim 47 , further comprising: 
 a mechanism configured to input subject data; and    wherein said estimating mechanism comprises a mechanism configured to estimate the strength of the bone based at least in part upon on the input subject data.    
     
     
         50 . The system of  claim 49 , wherein said inputting mechanism comprises: 
 a mechanism configured to input the age of the patient whose bone is being analyzed as said subject data.    
     
     
         51 . The system of  claim 47 , further comprising: 
 a mechanism configured to determine both of the Minkowski dimension for the bone and the trabecular orientation of the bone; and    a mechanism configured to input subject data of the patient whose bone is being analyzed;    wherein the estimating mechanism comprises a mechanism configured to estimate bone strength based on the measure of the Minkowski dimension, the trabecular orientation, and the subject data.    
     
     
         52 . The system of  claim 51 , wherein: 
 said determining mechanism comprises a mechanism configured to determine bone mineral density (BMD); and    said estimating mechanism comprises a mechanism configured to estimate the strength of the bone based at least in part upon on the determined BMD.    
     
     
         53 . The system of  claim 47 , further comprising: 
 a mechanism configured to predict the likelihood of bone fracture from the estimation of bone strength.    
     
     
         54 . The system of  claim 52 , further comprising: 
 a mechanism configured to predict the likelihood of bone fracture from the estimation of bone strength.    
     
     
         55 . The system of  claim 48 , wherein the mechanism configured to determine BMD comprises: 
 a mechanism configured to determine an area-based BMD as the measure of BMD.    
     
     
         56 . The system of  claim 48 , wherein the determining mechanism comprises: 
 a mechanism configured to determine a normalized BMD corresponding to a volumetric bone mineral density of the bone as the measure of BMD; and    wherein the estimating mechanism comprises a mechanism configured to estimate the strength of the bone based at least in part on the normalized BMD.    
     
     
         57 . The system of  claim 56 , wherein the mechanism configured to determine the normalized BMD comprises: 
 a mechanism configured to determine an area-based BMD of the bone;    a mechanism configured to perform bone geometry analysis to generate a measure of bone geometry; and    a mechanism configured to determine the normalized BMD from the area-based BMD and the measure of bone geometry.    
     
     
         58 . The system of  claim 57 , wherein the mechanism configured to perform bone geometry analysis comprises: 
 a mechanism configured to determine a neck width of the bone.    
     
     
         59 . The system of  claim 57 , wherein the mechanism configured to perform bone geometry analysis comprises: 
 a mechanism configured to determine a shaft width of the bone.    
     
     
         60 . The system of  claim 47 , further comprising: 
 a mechanism configured to select a region of interest (ROI) within the bone; and    a mechanism configured to perform texture analysis of the image data within the ROI to determine at least one measure of bone structure;    wherein the mechanism configured to estimate comprises a mechanism configured to estimate the strength of the bone based at least in part on the at least one measure of bone structure.    
     
     
         61 . The system of  claim 60 , wherein the a mechanism configured to perform texture analysis comprises: 
 a mechanism configured to extract fractal characteristics of the image data within the ROI using an artificial neural network, said at least one measure of bone structure including the fractal characteristics.    
     
     
         62 . The system of  claim 60 , wherein the a mechanism configured to perform texture analysis comprises: 
 a mechanism configured to determine a directional Minkowsi dimension for the image data within the ROI, said at least one measure of bone structure including the directional Minkowski dimension.    
     
     
         63 . The system of  claim 60 , wherein the a mechanism configured to perform texture analysis comprises: 
 a mechanism configured to determine a trabecular orientation for the image data within the ROI, said at least one measure of bone structure including the trabecular orientation.    
     
     
         64 . The system of  claim 56 , further comprising: 
 a mechanism configured to predict the likelihood of bone fracture from the estimation of bone strength.    
     
     
         65 . A system for the analysis of bone, comprising: 
 a mechanism configured to obtain digital image data corresponding to an image of the bone;    a mechanism configured to select a region of interest (ROI) within the bone;    a mechanism configured to extract a fractal characteristic of the image data within the ROI using an artificial neural network; and    a mechanism configured to estimate the strength of the bone based at least in part on the extracted fractal characteristic.    
     
     
         66 . The system of  claim 65 , wherein said extracting mechanism comprises: 
 a mechanism configured to perform fractal analysis of the image data within the ROI to generate slope data; and    a mechanism configured to input the slope data into the artificial neural network to generate information representative of bone strength.    
     
     
         67 . A system for the analysis of bone, comprising: 
 a mechanism configured to obtain digital image data corresponding to an image of the bone;    a mechanism configured to determine a measure of normalized bone mineral density (BMD) corresponding to a volumetric bone mineral density of the bone; and    a mechanism configured to estimate the strength of the bone based based at least in part on the normalized BMD.    
     
     
         68 . The system of  claim 67 , wherein the mechanism configured to determine the normalized BMD comprises: 
 a mechanism configured to determine an area-based BMD of the bone;    a mechanism configured to perform bone geometry analysis to generate a measure of bone geometry; and    a mechanism configured to determine the normalized BMD from the area-based BMD and the measure of bone geometry.    
     
     
         69 . The system of  claim 68 , further comprising: 
 a mechanism configured to predict the likelihood of bone fracture from the estimation of bone strength.