Systems and methods for predicting image quality scores of images

Abstract

Systems and methods are disclosed for identifying image acquisition parameters. One method includes receiving a patient data set including one or more reconstructions, one or more preliminary scans or patient information, and one or more acquisition parameters; computing one or more patient characteristics based on one or both of one or more preliminary scans and the patient information; computing one or more image characteristics associated with the one or more reconstructions; grouping the patient data set with one or more other patient data sets using the one or more patient characteristics; and identifying one or more image acquisition parameters suitable for the patient data set using the one or more image characteristics, the grouping of the patient data set with one or more other patient data sets, or a combination thereof.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method of predicting image quality scores of images for use in operating a medical imaging scanner, the method comprising:
 identifying one or more data acquisition device types;   receiving one or more data sets associated with each of the one or more data acquisition device types, wherein each data set of the one or more data sets includes one or more preliminary scans of a patient;   determining, based on the preliminary scans of the received one or more data sets, a predicted image quality score for an image produced by a data acquisition device type; and   identifying one or more recommended image acquisition parameters or a prediction of image quality for a new image based on the determined image quality score.   
     
     
         22 . The method of  claim 21 , wherein further comprising:
 determining a patient characteristic of the patient; and   determining the predicted image quality score further based on the patient characteristic of the patient.   
     
     
         23 . The method of  claim 21 , wherein the one or more data sets further includes one or more patient characteristics. 
     
     
         24 . The method of  claim 23 , further comprising:
 determining the one or more recommended image acquisition parameters using machine learning.   
     
     
         25 . The method of  claim 21 , further comprising:
 determining the predicted image quality score based on one or more imaging operator characteristics, one or more image characteristics, or one or more effects of imaging, wherein the one or more effects of imaging includes radiation exposure.   
     
     
         26 . The method of  claim 21 , wherein the predicted image quality score is determined using machine learning. 
     
     
         27 . The method of  claim 21 , further comprising:
 grouping the one or more data sets based on similarities between the preliminary scans respective to each of the one or more data sets; and   determining the predicted image quality score based on the grouping.   
     
     
         28 . The method of  claim 21 , further comprising:
 initiating or instructing production of an image based on the predicted image quality score.   
     
     
         29 . A system for predicting image quality scores of images for use in operating a medical imaging scanner, the system comprising:
 a data storage device storing instructions for determining predicted image quality scores of one or more images for use in operating a medical imaging scanner; and   a processor configured to execute the instructions to perform a method including:
 identifying one or more data acquisition device types; 
 receiving one or more data sets associated with each of the one or more data acquisition device types, wherein each data set of the one or more data sets includes one or more preliminary scans of a patient 
 determining, based on the preliminary scans of the received one or more data sets, a predicted image quality score for an image produced by a data acquisition device type; and 
 identifying one or more recommended image acquisition parameters or a prediction of image quality for a new image based on the determined image quality score. 
   
     
     
         30 . The system of  claim 29 , wherein the processor is further configured to perform the method comprising:
 determining a patient characteristic of the patient; and   determining the predicted image quality score further based on the patient characteristic of the patient.   
     
     
         30 . The system of  claim 29 , wherein the one or more data sets further includes one or more patient characteristics. 
     
     
         31 . The system of  claim 29 , wherein the system is further configured for:
 determining one or more recommended image acquisition parameters associated with the predicted image quality score.   
     
     
         32 . The system of  claim 29 , wherein the system is further configured for:
 determining the one or more recommended image acquisition parameters using machine learning.   
     
     
         33 . The system of  claim 29 , wherein the system is further configured for:
 determining the predicted image quality score based on one or more imaging operator characteristics, one or more image characteristics, or one or more effects of imaging, wherein the one or more effects of imaging includes radiation exposure.   
     
     
         34 . The system of  claim 29 , wherein the predicted image quality score is determined using machine learning. 
     
     
         35 . The system of  claim 29 , wherein the system is further configured for:
 grouping the one or more data sets based on similarities between the preliminary scans respective to each of the one or more data sets; and   determining the predicted image quality score based on the grouping.   
     
     
         36 . The system of  claim 29 , wherein the system is further configured for:
 initiating or instructing production of an image based on the predicted image quality score.   
     
     
         37 . A non-transitory computer readable medium for use on a computer system containing computer-executable programming instructions to perform operations for predicting image quality scores of images for use in operating a medical imaging scanner; the operation comprising:
 identifying one or more data acquisition device types;   receiving one or more data sets associated with each of the one or more data acquisition device types, wherein each data set of the one or more data sets includes one or more preliminary scans of a patient;   determining, based on the preliminary scans of the received one or more data sets, a predicted image quality score for an image produced by a selected data acquisition device type; and   identifying one or more recommended image acquisition parameters or a prediction of image quality for a new image based on the determined image quality score.   
     
     
         38 . The non-transitory computer readable medium of  claim 37 , the operations further comprising:
 determining a patient characteristic of the patient; and   determining the predicted image quality score further based on the patient characteristic of the patient.   
     
     
         39 . The non-transitory computer readable medium of  claim 37 , wherein the one or more data sets further includes one or more patient characteristics. 
     
     
         40 . The non-transitory computer readable medium of  claim 37 , the operations further comprising:
 determining the one or more recommended image acquisition parameters using machine learning.