Gordon Lecture: Learn Deeply to Advance Medical Imaging: Artificial Intelligence in MR and PET/MR

07/19/2019


Dr. Fang Liu is an assistant scientist at the University of Wisconsin School of Medicine and Public Health.  Dr. Liu obtained his Ph.D. in 2015 from Medical Physics at the University of Wisconsin and completed two years of postdoctoral training at the Radiology department. Dr. Liu has extensive research experience in the technical development of MR imaging for MR pulse sequence design, image reconstruction, quantitative imaging, and image analysis.
Below is a summary of his presentation

Medical imaging is a research field that remains plenty of technical and clinical challenges. The recent development of Artificial Intelligence, particularly Deep Learning (DL), has demonstrated high potentials to resolve such challenges. Dr. Liu presented some of his recent work for DL theory development and applications in medical imaging and will discuss the performance, strengths, and limitations. The talk gave an overview of DL in medical imaging and discuss some recent DL applications that successfully translate new learning-based approaches into performance improvement in MR and PET/MR imaging workflow.  One primary aim is to draw tightly connections between fundamental DL concepts and clinically relevant challenges in medical imaging. Topics covered rapid MR image acquisition, reconstruction and MR quantitative mapping, and image post-processing such as image segmentation and synthesis in MR and PET/MR, and finally lead to DL augmented disease diagnosis and prediction. The talk concluded with a discussion of open problems in DL that are particularly relevant to medical imaging and the potential challenges and opportunities in this emerging field.

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