• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    February 03, 2021: Dr. Pierre Ambrosini (Erasmus MC, Netherlands), Automatic Detection of Cribriform Growth Pattern in Prostate Histology Images

    Cribriform growth patterns in prostate carcinoma are associated with poor prognosis. We aimed to introduce a method to detect such patterns automatically. To do so, convolutional neural network was trained to detect cribriform growth patterns. To benchmark method performance, intra- and inter-observer variability has been evaluated. In the presentation we will discuss the method, the experiments and the results of our detection algorithm.

    Speaker: Dr. Pierre Ambrosini, Erasmus MC

    Time: 15:30, Wednesday, February 03, 2021

    Venue: G2-315, 144 Xuan Thuy, Cau Giay, Hanoi

    speaker

    Pierre Ambrosini received a Master in Computer Science from the University of Lyon (France). He worked as a research engineer at the Biomedical Imaging Group Rotterdam (BIGR) in Erasmus MC. With his group, he prototyped a workstation that aims at improving image guidance during medical interventions. Afterward, he continued his research in the same group as a Ph.D. candidate on image guidance for the Transcatheter Arterial ChemoEmbolization procedure. The research was a collaboration with Philips Healthcare. His research mainly revolved around real-time registration, tracking, and segmentation with X-ray images. After his Ph.D. project, he has been in a postdoctoral position at the Imaging Physics department of the Delft University of Technology working on automatic detection of tumor growth patterns in prostate histopathology images. Since September 2020, he is now back in Erasmus MC at the BIGR and the surgery department working on augmented reality in surgical oncology.

    SAME CATEGORY

    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, […]