Abstract: 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.

Abstract: 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.

Abstract: The invention provides a method and clinical data mining system for enabling a user to derive knowledge from data corresponding to a plurality of electronic health records stored in a repository. One or more data elements are provided as an input. The data elements may include textual reports, images, and one or more criteria specified by the user. Information is extracted from one or more images associated with one or more electronic health records stored in the repository, based on the data elements. Further, information is extracted from one or more textual reports and structured data associated with the one or more electronic health records. Thereafter, one or more reports are generated based on the extracted information to enable the user to analyze the information. Subsequently, the user may derive knowledge from the data based on the analysis.