Abstract: Disclosed embodiments include methods and computer systems for brain image prediction or segmentation. A clinical image file of data representative of a patients' brain image, including structures of interest (SOI) such as the subthalamic nucleus (STN), is applied to and processed by a segmentation process. The segmentation process uses one or more machine learning approaches such as trained deep learning models to identify the SOI in the clinical image. Output by the segmentation process is a segmented image file of data representing the brain image in which the structures of interest (SOI) are segmented. By the segmentation process, the SOI in clinical image, including the locations, orientations and/or boundaries of the SOI, are accurately predicted or identified, and can thereby be presented in an enhanced visualization form (e.g., highlighted) in the segmented image.