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X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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DTSTART:20240101T000000
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DTSTART;TZID=Asia/Hong_Kong:20250815T110000
DTEND;TZID=Asia/Hong_Kong:20250815T120000
DTSTAMP:20260509T210748
CREATED:20250806T043442Z
LAST-MODIFIED:20250806T090812Z
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SUMMARY:Seminar on Towards Deep Learning MR Reconstruction with No Ground Truth and Fast Inference
DESCRIPTION:Abstract\nSince 2016\, deep learning techniques have been introduced to solve the inverse problem of MR image reconstruction from undersampled data from accelerated acquisitions. Since then\, the field has grown substantially. A wide range of machine learning methods have been developed\, translated into clinical practice and adopted as products by all major scanner vendors. In this talk\, after a general introduction to deep learning for MR image reconstruction\, I will focus on two open challenges in the field. First\, the application of deep learning reconstruction for dynamic contrast-enhanced imaging and abdominal imaging\, where no ground truth can be obtained for model training. Second\, the optimisation of network architectures towards computation time at inference for real-time imaging and clinical translation of instance-specific learning\, where trainings need to be performed during inference. \nSpeaker\nProf. Florian KNOLL\nProfessor and Head of the Computational Imaging Lab\,\nDepartment Artificial Intelligence in Biomedical Engineering (AIBE)\,\nFriedrich-Alexander-Universität Erlangen-Nürnberg \nSpeaker’s Biography\nProf. Florian KNOLL received his PhD in Electrical Engineering in 2011 from Graz University of Technology. From 2015 to 2021\, he was Assistant Professor for Radiology at the Center for Biomedical Imaging at NYU Grossman School of Medicine. Since 2021\, he has been Professor and Head of the Computational Imaging Lab at the Department Artificial Intelligence in Biomedical Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg. He currently holds four grants from the German Research Fund (DFG) and an R01 grant from the National Institutes of Health (NIH). His research interests include iterative MR image reconstruction\, parallel MR imaging\, compressed sensing and machine learning. \nOrganiser\nProf. Ed Xuekui WU\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome!
URL:https://ece.hku.hk/events/20250815-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/08/1280.jpg
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