Detecting and classifying medical images based on continuously-learning whole body landmarks detections

A computer-implemented method for automatically generating metadata tags for a medical image, the method comprising:

• receiving a medical image;
• identifying a set of body landmarks in the medical image;
• applying one or more machine learning models to the set of body landmarks to identify anatomical objects present in the image;
• generating one or more metadata tags corresponding to the anatomical objects;
• storing the metadata tags in the medical image;
• transferring the medical image with the metadata tags to a data repository;
• receiving user feedback comprising a modification to one or more of the metadata tags associated with the medical image stored in the data repository;
• and
• retraining the one or more machine learning models based on the received modification.

A system for automatically generating metadata tags for a medical image, the method comprising:

• a medical image scanner configured to acquire a medical image;
• and
• an image processing system comprising one or more processors configured to
• automatically identify a set of body landmarks in the medical image;
• identify anatomical objects present in the image based on the set of body landmarks;
• generate, using a program module configured to identify anatomical objects present in the image from the set of body landmarks, one or more metadata tags corresponding to the anatomical objects;
• store the metadata tags in the medical image;
• transfer the medical image with the metadata tags to a data repository;
• receive user feedback comprising a modification to one or more of the metadata tags associated with the medical image stored in the data repository;
• and
• adjust the program module based on the received modification.