Systems and methods for automated patient anatomy and orientation identification using an artificial intelligence (AI) based deep learning module are provided. The method comprises positioning a subject over a table of a magnetic resonance imaging (MRI) system and wrapping at least one radiofrequency (RF) imaging coil over the subject. The method comprises obtaining a plurality of depth images, color images and infrared images of the subject using a three-dimensional (3D) depth camera and identifying the table boundary of the MRI system using the images obtained by the 3D camera. The method further comprises identifying a location of the subject over the table to determine if the subject is positioned within the table boundary of the MRI system and identifying a plurality of key anatomical points or regions corresponding to a plurality of organs of the subject body. The method further comprises identifying all DICOM orientations of the subject over the table of the MRI system and identifying the coils of the MRI system wrapped around the subject body and determining the orientation of the subject with respect to the coils of the MRI system, hospital gown, and blankets. The method further comprises identifying the anatomical key points occluded by the coils of the MRI system, hospital gown, and blankets to determine accurate positioning of the coils of the MRI system over the subject anatomy for automated landmarking of anatomies and imaging.