Abstract: Disclosed herein is a medical system (100, 300, 500) comprising a memory (110) storing machine executable instructions (120) and a B0 field estimation module (126); and a computational system (106). Execution of the machine executable instructions causes the computational system to receive (200) an initial magnetic resonance image (122) that comprises a magnitude component and is descriptive of a first region (326) of interest of a subject (118).

Abstract: Systems and methods are disclosed for generating device test cases for medical imaging devices, which are not only reflective of current actual field usage of the device but also provide outlook on future usage. A probabilistic model of usage patterns is generated from historic data present in the device field logs by mining the current usage patterns. A Deep Long Short Term Memory Neural Network model of the usage patterns is constructed to predict the future usage patterns. Additionally, to capture the changing trends of device usage patterns in the field, predictive models are continuously updated in real time, and the test cases generated log files by the models are integrated into an automated testing system.

Abstract: Systems and methods are disclosed for generating device test cases for medical imaging devices, which are not only reflective of current actual field usage of the device but also provide outlook on future usage. A probabilistic model of usage patterns is generated from historic data present in the device field logs by mining the current usage patterns. A Deep Long Short Term Memory Neural Network model of the usage patterns is constructed to predict the future usage patterns. Additionally, to capture the changing trends of device usage patterns in the field, predictive models are continuously updated in real time, and the test cases generated log files by the models are integrated into an automated testing system.