Apparatus for predicting metadata of medical image and method thereof

Abstract

This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.

What is claimed is: 
     
         1 . A computerized medical image analysis method, using a hardware processor and a hardware memory, comprising:
 machine-training a prediction model for predicting metadata of an input medical image based on a plurality of image-metadata sets;   processing the input medical image to obtain predicted metadata of the input medical image, wherein the predicted metadata comprises at least one of information related to one or more objects included in the input medical image, information about a shooting environment of the input medical image, information about patient corresponding to the input medical image, and information related to a display method of the input medical image; and   processing the input medical image to detect at least one of abnormality in the input medical image based on the predicted metadata,   wherein the plurality of image-metadata sets comprise a plurality of digital imaging and communications in medicine (DICOM) files each comprising a DICOM image file and a DICOM header.   
     
     
         2 . The method of  claim 1 , further comprising adjusting the input image using predicted metadata, wherein the display method information comprises at least one of window center information, window width information, color inversion information, image rotation information, and image flip information of the input medical image. 
     
     
         3 . The method of  claim 2 , wherein adjusting the input medical image comprises adjusting at least one of a window center, a window width, a color, and an output direction of the input medical image based on the predicted metadata. 
     
     
         4 . The method of  claim 1 , wherein the plurality of image-metadata sets comprise a training medical image and metadata of the training medical data, and the input medical image is obtained from an input DICOM tile comprising an input DICOM header of the input medical image. 
     
     
         5 . The method of  claim 1 , wherein the shooting environment of the input medical image includes modality information of the input medical image, and
 wherein the processing the input medical image to detect at least one abnormality comprises detecting at least one of abnormality in the input medical image based on a prediction model corresponding to the modality information included in the predicted metadata.   
     
     
         6 . The method of  claim 1 , further comprising matching and saving the predicted metadata of the input medical image in association with the input medical image. 
     
     
         7 . The method of  claim 1 , further comprising verifying whether body part information of the predicted metadata matches a target body part for which abnormality is to be detected. 
     
     
         8 . The method of  claim 1 , further comprising verifying whether modality information of the predicted metadata is appropriate for detecting anomaly. 
     
     
         9 . The method of  claim 1 , further comprising verifying whether patient information of predicted metadata is appropriate for detecting abnormality. 
     
     
         10 . A medical image analysis apparatus comprising a memory storing computer-executable instructions and a processor configured to execute the computer-executable instructions,
 wherein the processor is configured, b executing the computer-executable instructions, to perform:
 machine-training a prediction model for predicting metadata of an input medical image based on a plurality of image-metadata sets; 
 processing the input medical image to obtain predicted metadata of the input medical image, wherein the predicted metadata comprises at least one of information related to one or more objects included in the input medical image, information about a shooting environment of the input medical image, information about patient corresponding to the input medical image, and information related to a display method of the input medical image; and 
 processing the input medical image to detect at least one of abnormality in the input medical image based on the predicted metadata, 
 wherein the plurality of image-metadata sets comprise a plurality of digital imaging and communications in medicine (DICOM) files each comprising a DICOM image file and a DICOM header. 
   
     
     
         11 . The apparatus of  claim 10 , wherein the processor is further configured, by executing the computer-executable instructions, to perform adjusting the input image using predicted metadata, and wherein the display method information comprises at least one of window center information, window width information, color inversion information, image rotation information, and image flip information of the input medical image. 
     
     
         12 . The apparatus of  claim 11 , wherein the processor is further configured to perform adjusting the input medical image comprises adjusting at least one of a window center, a window width, a color, and an output direction of the input medical image based on the predicted metadata. 
     
     
         13 . The apparatus of  claim 10 , wherein the plurality of image-metadata sets comprise a training medical image and metadata of the training medical data, and the input medical image is obtained from an input DICOM file comprising an input DICOM header of the input medical image. 
     
     
         14 . The apparatus of  claim 10 , wherein the shooting environment of the input medical image includes modality information of the input medical image, and
 wherein the processing the input medical image to detect at least one abnormality comprises detecting at least one of abnormality in the input medical image based on a prediction model corresponding to the modality information included in the predicted metadata.   
     
     
         15 . The apparatus of  claim 10 , wherein the processor is further configured, by executing the computer-executable instructions, to perform matching and saving the predicted metadata of the input medical image in association with the input medical image. 
     
     
         16 . The apparatus of  claim 10 , wherein the processor is further configured, by executing the computer-executable instructions, to perform verifying whether body part information of the predicted metadata matches a target body part for which abnormality is to be detected. 
     
     
         17 . The apparatus of  claim 10 , wherein the processor is further configured, by executing the computer-executable instructions, to perform verifying whether modality information of the predicted metadata is appropriate for detecting anomaly. 
     
     
         18 . The apparatus of  claim 10 , wherein the processor is further configured, by executing the computer-executable instructions, to perform verifying whether patient information of predicted metadata is appropriate for detecting abnormality.