• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    November 24, 2020: Prof. Theo van Walsum (Erasmus MC, Netherlands), Image guidance in interventions and therapy

    Minimally invasive interventions are beneficial for patients, but come at the expense of the physician: tactile and visual feedback is often limited. Traditionally, navigation systems have been used to assist physicians in (minimally invasive) interventions. Such systems are not applicable in minimally invasive interventions in soft tissue. At the BIGR group, we have been developing and assessing multimodal image guided navigation approaches for minimally invasive interventions in soft tissue. In the presentation, we will detail and discuss some of these approaches, e.g. for TACE, PCI, TIPS and RFA. In addition, we will discuss current developments and the impact of deep learning on the developments in this field.

    Speaker: Prof. Theo van Walsum, Erasmus MC

    Time: 15:30, Tuesday, November 24, 2020

    Venue: E3-212, 144 Xuan Thuy, Cau Giay, Hanoi


    Theo van Walsum graduated in Informatics (Computer Science) at the Delft University of Technology in 1990. In 1995 he received his PhD at Scientific Visualization Group of Delft University of Technology. Subject of his thesis was flow visualization on curvilinear grids. From June 1995 to May 1996, he was a research fellow at the Laboratory of Clinical and Experimental Image Processing (LKEB), at the University Hospital Leiden, where he worked on visualization of MRI and MRA data. From June 1996 to January 2005, he worked as a Postdoc at the Image Sciences Institute at the UMC Utrecht, on simulation and visualization for endovascular treatment of AAA, the image processing software environment, catheter tracking for image guidance and image guidance using 3D Rotational X-Ray imaging. Since 2005, he is heading the “Image Guidance in Interventions” theme group at the Biomedical Imaging Group Rotterdam. His interests are medical imaging, image guidance and navigation, visualization and software engineering.


    February 2, 2024: Dr. Khoa D. Doan (Vin Univeristy) Toward Reliable and Practical Machine Learning Applications

    While Machine Learning (ML) has rapidly transformed several domains and applications with incredible successes, there are also important areas where the progress is significantly slower. Specifically, there exists a widened complexity gap between the methods currently investigated in research and those used in practice in these areas. One reason is that many algorithms, despite achieving […]

    February 2, 2024: Prof. Heng Ji (University of Illinois at Urbana-Champaign), Combating with Misinformation and Cancer: A Unified Multimodal AI Approach to Healthy and Happy Life

    A research overview of ongoing research projects, especially focusing on two that are most related to the VinUni-UIUC Smart Health Center: (1) Misinformation Detection and Trustworthy Large Language Models; (2) Joint Natural Language and Molecule Learning for Drug Discovery. Unsurprisingly these two seemingly different research problems can be tackled with a unified approach based on […]

    January 11, 2024: Dr. Le Duc Trong (FIT-UET) Resilient Multimodal Learning for Multimodal Emotion Recognition in the Presence of Incomplete Modalities

    Multimodal Emotion Recognition in Conversation (Multimodal ERC) is a critical area of research for interpreting human communication in diverse applications. Nevertheless, the persistent issue of uncertain missing modalities poses a major hurdle, hampering the development of robust Multimodal ERC models. Existing approaches face limitations in effectively leveraging a fusion of diverse data modalities encompassing audio, […]