• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    February 26, 2019: Mr. Nguyen Thanh Trung (AVITECH), CT Image Denoising Using Sparse Representation

    X-ray computed tomography (CT) is now a widely used imaging modality for numerous medical purposes. Due to the biological risk of x-ray radiation, developing CT methodologies minimizing x-ray exposure to patients while achieving the clinical tasks has been a major concern. However, reducing the radiation dose as in low-dose CT techniques results in images that are often degraded by noise and artifacts. We present here two methods for denoising of low-dose CT images. In the first method, a noisy image is decomposed into three frequency bands namely low-band, middle-band and high-band such that the noise component mainly is presented in the middle and high bands. Then, by exploiting the fact that a small patch of the noisy image can be approximated by a linear combination of several elements in a given dictionary of noise-free image patches, generated from noise-free CT images taken at nearly the same position with the noisy image, noise on these two bands is effectively eliminated. In the second method, the noisy image is denoised patch-wise in which each noisy patch is estimated by a sparse representation using a dictionary of patches built from noise-free example images, which are similar to the noisy image. Experimental results conducted on both synthetic and real noise data demonstrated the efficiency of the proposed methods.

    Speaker: Mr. Nguyen Thanh Trung, AVITECH

    Time: 15:30, Tuesday, February 26, 2019

    Venue: E3-707, 144 Xuan Thuy, Cau Giay, Hanoi

    speaker

    Nguyen Thanh Trung received his B.Eng.degree in Electronics and Telecommunicationsfrom the Faculty of Technology, Vietnam Na-tional University, Hanoi, Vietnam in 2003, M.S.degree in electronics engineering from Uni-versity of Engineering and Technology, Viet-nam National University, Hanoi, Vietnam in 2012. He is now a Phd student at VNU-UET and a lecturer at the Faculty of Electronics and Communication, University of Information and Communication Technology, Thainguyen University, Vietnam. His research interests include biomedicalsignal and image processing,sparse coding, machine learning.

    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, […]