System and methods for classifying magnetic resonance imaging (MRI) image characteristics

A method comprising receiving medical imaging data associated with a magnetic resonance imaging (MRI) scan, determining pulse sequence characteristics for the imaging data using a machine learning (ML) model, classifying the characteristics, and updating a database containing the imaging data to include the classified characteristics. Feature extraction may be applied to the imaging data prior to determining the characteristics. The imaging data and characteristics may be displayed to the user via an interface (GUI). A hanging protocol may be determined based on the characteristics and the imaging data displayed according to the hanging protocol. The ML model may be a convolutional neural network (CNN). The characteristics may include one of: whether fat suppression is present, an echo type of the MRI scan, an indication of whether fluid is bright, or whether a contrast is present. A DICOM tag may be generated for the imaging data based on the classification.