Motion artifact reduction is one of the important research topics in MR imaging, as the motion artifact degrades image quality and makes diagnosis difficult. Recently, many deep learning approaches have been studied for motion artifact reduction. Unfortunately, most existing models are trained in a supervised manner, requiring paired motion-corrupted and motion-free images, or are based on a strict motion-corruption model, which limits their use for real-world situations.
The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 100 of its members to the grade of IEEE Senior Member. These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest.
The Signal Processing Society (SPS) conducts webinars presented by professionals in the field of signal processing and related technologies on an ongoing basis. Webinars are also hosted periodically by SPS Technical Committees, and other network of communities. Visit the Upcoming Events page to see a list of our upcoming webinars and join us! Visit the SPS BLOG for more related content on a regular basis!
Date: 6 August 2024
Time: 1:00 PM ET (New York Time)
Presenter(s): Dr. Shinji Watanabe, Dr. Abdelrahman Mohamed
Dr. Karen Livescu, Dr. Hung-yi Lee, Dr. Tara Sainath,
Dr. Katrin Kirchhoff & Dr. Shang-Wen Li