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Robust and conditional deep learning based medical image registration
Speaker: Prof. Albert CHUNG Department of Computer Science University of Exeter Title: "Robust and conditional deep learning based medical image registration" Date: Monday, 6 February 2023 Time: 3:00pm - 4:00pm HKT Zoom link: https://hkust.zoom.us/j/465698645?pwd=aVRaNWs2RHNFcXpnWGlkR05wTTk3UT09 Meeting ID: 465 698 645 Passcode: 20222023 Abstract: Medical imaging, such as magnetic resonance imaging and computed tomography, produces high-quality, high-resolution images that reveal the anatomical and functional structures of the human body. For example, neuroimages can delineate details of brain tissues and structures and contribute to the diagnosis of brain diseases and the detection of biomarkers for early treatment. To analyze images, image registration needs to be performed to highlight anatomical changes over time, transfer segmentation labels for interpretation, or aid image-guided surgery. The registration of images with large anatomical deformation, e.g., tumors, is a challenging task due to the implicit assumption of small deformation settings in conventional methods. In this talk, I will give an overview of our recently developed image registration methods, which rely on the deep Laplacian pyramid networks, a controllable regularization module, and a multi-resolution alignment strategy. The new methods can mitigate the problems arising from images with large anatomical deformation and offer accurate image registration results. At the end of the talk, I will introduce some possible research directions for medical image analysis. Biography: Albert Chung is currently a Chair in AI at the Department of Computer Science, University of Exeter, and Professor Emeritus and Adjunct Professor at the Department of Computer Science and Engineering, HKUST. He received his BEng (First-Class Honors) in Computer Engineering from the University of Hong Kong in 1995. He joined HKUST in 1996 and obtained his MPhil in Computer Science in 1998. He was awarded the Croucher Foundation scholarship in 1998 to read DPhil in Engineering Science at the Medical Vision Laboratory, University of Oxford. He graduated in 2001 with the BMVA Best Thesis Award in the UK. He was a visiting scientist at the AI Laboratory, Massachusetts Institute of Technology, in 2001-02 and had been with HKUST since then until 2021. He served as the CPEG Director (2010-12), Associate Head of CSE (2016-19) and Associate Dean of Engineering at SENG HKUST (Jan 2020 - Dec 2021). His research interests include medical image analysis, image processing and computer vision. His research focus is to create and apply computational techniques in medical image analysis, and the ultimate goal is to improve the quality of healthcare services. He received two Best Paper Awards in MIAR'16 and DLMIA'15. He is active in his research community. He co-chaired and hosted the international conference on Information Processing in Medical Imaging (IPMI) in 2019 at HKUST and served as the Chair of the IPMI Conference Board in 2019-21. He was the Tutorial Chair for the IEEE International Symposium on Biomedical Imaging in 2019. He is serving as one of the Editorial Board members for the Medical Image Analysis journal and the Journal of Computerized Medical Imaging and Graphics.