Abstract: Described herein are neural network-based systems, methods and instrumentalities associated with estimating the motion of an anatomical structure. The motion estimation may be performed using a feature pyramid and/or a motion pyramid that correspond to multiple image scales. The motion estimation may be performed using neural networks and parameters that are learned via a training process involving a student network and a teacher network pre-pretrained with abilities to apply progressive motion compensation.

Abstract: Described herein are neural network-based systems, methods and instrumentalities associated with imagery data processing. The neural networks may be pre-trained to learn parameters or models for processing the imagery data and upon deployment the neural networks may automatically perform further optimization of the learned parameters or models based on a small set of online data samples. The online optimization may be facilitated via offline meta-learning so that the optimization may be accomplished quickly in a few optimization steps.

Abstract: Described herein are systems, methods and instrumentalities associated with motion tracking and strain determination. A motion tracking apparatus as described herein may track the motion of an anatomical structure from a source image to a target image and determine corresponding points on one or more surfaces of the anatomical structure in both the source image and the target image. Using these surface points, the motion tracking apparatus may calculate one or more strain parameters associated with the anatomical structure and provide the strain parameters for medical diagnosis and/or treatment.

Abstract: Described herein are neural network-based systems, methods and instrumentalities associated with estimating the motion of an anatomical structure. The motion estimation may be performed using a feature pyramid and/or a motion pyramid that correspond to multiple image scales. The motion estimation may be performed using neural networks and parameters that are learned via a training process involving a student network and a teacher network pre-pretrained with abilities to apply progressive motion compensation.

Abstract: Described herein are systems, methods and instrumentalities associated with motion tracking and strain determination. A motion tracking apparatus as described herein may track the motion of an anatomical structure from a source image to a target image and determine corresponding points on one or more surfaces of the anatomical structure in both the source image and the target image. Using these surface points, the motion tracking apparatus may calculate one or more strain parameters associated with the anatomical structure and provide the strain parameters for medical diagnosis and/or treatment.

Abstract: Described herein are neural network-based systems, methods and instrumentalities associated with imagery data processing. The neural networks may be pre-trained to learn parameters or models for processing the imagery data and upon deployment the neural networks may automatically perform further optimization of the learned parameters or models based on a small set of online data samples. The online optimization may be facilitated via offline meta-learning so that the optimization may be accomplished quickly in a few optimization steps.