University of Birmingham > Talks@bham > Data Science and Computational Statistics Seminar > Deep Learning Meets Medical Imaging: From Signals to Clinically Useful Information

Deep Learning Meets Medical Imaging: From Signals to Clinically Useful Information

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Machine Learning has shown great potential in improving the entire medical imaging workflow, from image acquisition and reconstruction, to disease diagnosis and treatment. This talk will focus on the recent advances of deep learning in medical imaging for the discovery and quantification of clinically useful information. The talk will describe how model-based deep learning can be used for MRI reconstruction from undersampled data and will discuss about one of its applications to accelerated dynamic cardiac MRI cine imaging. It will also show the clinical utility of applications of deep learning for the analysis of medical images such as anatomical structure segmentation, mono-/multi-modal image registration and myocardial motion tracking. Finally, it will be discussed about the integration of MRI reconstruction and analysis, which may potentially facilitate an AI-enabled imaging pipeline.

This talk is part of the Data Science and Computational Statistics Seminar series.

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