Patient-Specific Deep Learning Tracking Framework for Real-Time 2D Target Localization in Magnetic Resonance Imaging-Guided Radiation Therapy.

Purpose: We propose a tumor tracking framework for 2D cine magnetic resonance imaging (MRI) based on a pair of deep learning (DL) models relying on patient-specific (PS) training.

Methods And Materials: The chosen DL models are: (1) an image registration transformer and (2) an auto-segmentation convolutional neural network (CNN). We collected over 1,400,000 cine MRI frames from 219 patients treated on a 0.