Systems and methods for improved analysis and generation of medical imaging reports

Abstract

Systems and methods for the improved analysis and generation of medical imaging reports are disclosed. In particular, the present disclosure provides systems and methods that may be used for the automated analysis of radiological information, such as medical images and related text statements for discrepancy analysis, accuracy analysis and quality assurance. Systems and methods may include receiving medical images and textual data, generating enhanced medical image data by applying an artificial intelligence module to the received medical images, generating structured text data by applying a natural language processing module to the received textual data, and generating improved medical image reports and/or alerts based on the generated enhanced medical image data and the generated structured text data.

1 . A system for providing computer-aided detection of clinical interest areas captured in medical images, the system comprising:
 a server system configured to receive the medical images and textual data, wherein the server system comprises:   an image processing unit configured to apply an artificial intelligence computer vision techniques to the received medical images to generate enhanced medical image data;   a text processing unit configured to apply natural language processing to the received textual data to generate structured text data; and   a platform configured to detect clinical interest areas by detecting one or more discrepancies between the generated enhanced medical image data, the generated structured text data, and the received medical image and textual data.   
     
     
         2 . The system of  claim 1 , wherein the platform is further configured to generate an alert responsive to the detected discrepancies. 
     
     
         3 . The system of  claim 1 , wherein the artificial intelligence computer vision techniques comprises a convolutional neural network. 
     
     
         4 . The system of  claim 1 , wherein the server system comprises a processing module configured to dispatch data and receive results from the image processing unit and the text processing unit. 
     
     
         5 . The system of  claim 1 , wherein the platform is further configured to generate at least one of a clinical or non-clinical interface including the enhanced medical image data. 
     
     
         6 . The system of  claim 1 , wherein the platform is further configured to incorporate the enhanced medical image data into an findings record. 
     
     
         7 . The system of  claim 1 , wherein the natural language processing comprises at least one recurrent neural network. 
     
     
         8 . A method for generating improved medical image reports comprising:
 receiving medical images and textual data;   generating enhanced medical image data by applying an artificial intelligence module to the received medical images;   generating structured text data by applying a natural language processing module to the received textual data;   determining discrepancies between a received medical image report and the generated enhanced medical image data and the generated structured text data; and   generating an improved medical image report including at least one of the generated enhanced medical image data, generated structured text data, and determined discrepancies.   
     
     
         9 . The method of  claim 8 , further comprising:
 providing an alert to at least one of a user or a creator of the medical image report responsive to determining a discrepancy.   
     
     
         10 . The method of  claim 8 , wherein applying an artificial intelligence module comprises applying a convolutional neural network. 
     
     
         11 . The method of  claim 10 , comprising:
 training at least a regression convolutional neural network, a semantic segmentation convolutional network and a classification convolutional neural network.   
     
     
         12 . The method of  claim 8 , wherein applying a natural language processing module to the received textual data further comprises applying a recurrent neural network. 
     
     
         13 . The method of  claim 8 , comprising:
 generating at least one of a clinical or non-clinical interface including the generated improved medical image report.   
     
     
         14 . The method of  claim 8 , comprising:
 incorporating the generated improved medical image report into a findings record.   
     
     
         15 . The method of  claim 8 , wherein determining discrepancies between a received medical image report and the generated enhanced medical image data and the generated structured text data comprises:
 identifying and storing each finding indicated in the enhanced medical image data;   correlating each finding to its corresponding structured text data;   identifying corresponding portions for each finding in a radiology report;   identifying discrepancies between the corresponding portions and the corresponding structured text data for each finding; and   augmenting the radiology report with the identified discrepancies.   
     
     
         16 . The method of  claim 15 , further comprising:
 presenting the generated improved medical image report to a physician for approval.   
     
     
         17 . A non-transitory computer-readable medium storing instructions that, when executed on one or more processors, cause the one or more processors to:
 receive medical images;   receive textual data;   generate enhanced medical image data by applying an artificial intelligence module to the received medical images;   generate structured text data by applying a natural language processing module to the received textual data; and   generate an improved medical image report including at least one of the generated enhanced medical image data, generated structured text data, and determined discrepancies.   
     
     
         18 . The non-transitory computer-readable medium of  claim 17 , wherein generating the enhanced medical image data comprises applying a convolutional neural network. 
     
     
         19 . The non-transitory computer-readable medium of  claim 17 , wherein applying a natural language processing module to the received textual data further comprises applying at least one recurrent neural network. 
     
     
         20 . The non-transitory computer-readable medium of  claim 17 , wherein generating an improved medical image report comprises the one or more processors being configured to:
 identify and store each finding indicated in the enhanced medical image data;   correlate each finding to its corresponding structured text data;   identify corresponding portions for each finding in a radiology report;   identify discrepancies between the corresponding portions and the corresponding structured text data for each finding; and   augmenting the radiology report with the identified discrepancies.