Systems and methods for determining quality metrics of an image or images based on an edge gradient profile and characterizing regions of interest in an image or images

Abstract

Disclosed herein are systems and methods for determining quality metrics of images based on an edge gradient profile and characterizing regions of interest in an image or images. According to an aspect, a method includes using an imaging device to acquire one or more images including at least a portion of an organ of a subject. The method also includes computing an edge profile across an organ interface of a subject. The method also includes computing an edge gradient profile from the edge profile of a subject. The method also includes computing a image quality metric related to the spatial resolution of the image or images from the edge gradient profile. The method also includes defining multiple regions of interest within the portion of the organ. Further, the method includes characterizing the regions of interest based on predetermined criteria. The method also includes presenting the characterization of the edge gradient profile and characterization of the regions of interest to a user.

1 - 13 . (canceled) 
     
     
         14 . A method comprising:
 using an imaging device to acquire one or more images including at least a portion of an organ of a subject;   defining a plurality of regions of interest within the portion of the organ;   characterizing the regions of interest based on predetermined criteria; and   presenting the characterization of the regions of interest to a user.   
     
     
         15 . The method of  claim 14 , wherein the organ is one of a lung and liver. 
     
     
         16 . The method of  claim 14 , wherein the one or more acquired images are one of contrast enhanced or non-contrast enhanced images. 
     
     
         17 . The method of  claim 14 , wherein using the imaging device comprises using a computed tomography (CT) imaging device to acquire one or more CT images of the at least a portion of the organ of the subject. 
     
     
         18 . The method of  claim 14 , defining the plurality of regions of interest comprises applying a thresholding technique to the one or more images. 
     
     
         19 . The method of  claim 14 , further comprising defining an area of the at least the portion of the organ of the subject within the one or more images. 
     
     
         20 . The method of  claim 19 , wherein defining the area comprises using an Otsu thresholding technique to segment the organ of the subject. 
     
     
         21 . The method of  claim 14 , wherein defining the area comprises automatically defining the area of the at least a portion of the organ. 
     
     
         22 . The method of  claim 14 , wherein characterizing the regions of interest comprises automatically characterizing statistics of voxel values inside the regions of interest. 
     
     
         23 . The method of  claim 14 , wherein defining the plurality of regions of interest comprises:
 generating an intensity map of the potential regions of interest; and   using the intensity map to define the regions of interest.   
     
     
         24 . The method of  claim 23 , wherein characterizing the regions of interest comprises generating a histogram based on the intensity map. 
     
     
         25 . The method of  claim 24 , wherein generating the histogram comprises generating the histogram based on a number of Hounsfield units within the regions of interest. 
     
     
         26 . The method of  claim 25 , further comprising applying statistics to the histogram to result in the characterization of the regions of interest. 
     
     
         27 - 39 . (canceled) 
     
     
         40 . A system comprising:
 an imaging device configured to acquire one or more images including at least a portion of an organ of a subject; and   a computing device comprising at least one processor and memory that:
 defines a plurality of regions of interest within the portion of the organ; 
 characterizes the regions of interest based on predetermined criteria; and 
 presents the characterization of the regions of interest to a user. 
   
     
     
         41 . The system of  claim 40 , wherein the organ is one of a lung and liver. 
     
     
         42 . The system of  claim 40 , wherein the one or more acquired images are one of contrast enhanced or non-contrast enhanced images. 
     
     
         43 . The system of  claim 42 , wherein using the imaging device comprises using a computed tomography (CT) imaging device to acquire one or more CT images of the at least a portion of the organ of the subject. 
     
     
         44 . The system of  claim 42 , defining the plurality of regions of interest comprises applying a thresholding technique to the one or more images. 
     
     
         45 . The system of  claim 42 , further comprising defining an area of the at least the portion of the organ of the subject within the one or more images. 
     
     
         46 . The system of  claim 45 , wherein defining the area comprises using an Otsu thresholding technique to segment the organ of the subject. 
     
     
         47 . The system of  claim 42 , wherein defining the area comprises automatically defining the area of the at least a portion of the organ. 
     
     
         48 . The system of  claim 42 , wherein characterizing the regions of interest comprises automatically characterizing statistics of voxel values inside the regions of interest. 
     
     
         49 . The system of  claim 42 , wherein defining the plurality of regions of interest comprises:
 generating an intensity map of the potential regions of interest; and   using the intensity map to define the regions of interest.   
     
     
         50 . The system of  claim 49 , wherein characterizing the regions of interest comprises generating a histogram based on the intensity map. 
     
     
         51 . The system of  claim 50 , wherein generating the histogram comprises generating the histogram based on a number of Hounsfield units within the regions of interest. 
     
     
         52 . The system of  claim 51 , further comprising applying statistics to the histogram to result in the characterization of the regions of interest.