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Found 3 papers, 1 papers with code
MR-Contrast-Aware Image-to-Image Translations with Generative Adversarial Networks
Our approach is motivated by style transfer networks, whereas the "style" for an image is explicitly given in our case, as it is determined by the MR acquisition parameters our network is conditioned on.
Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adversarial Networks
A Magnetic Resonance Imaging (MRI) exam typically consists of the acquisition of multiple MR pulse sequences, which are required for a reliable diagnosis.
System Design for a Data-driven and Explainable Customer Sentiment Monitor
The overall framework is currently deployed, learns and evaluates predictive models from terabytes of IoT and enterprise data to actively monitor the customer sentiment for a fleet of thousands of high-end medical devices.
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