Special Session 1 - Artificial Intelligence in Medical Image Analysis

  • Submission Link: https://www.easychair.org/conferences/?conf=prai2024
    (Select Track Special Session 1: Artificial Intelligence in Medical Image Analysis)

    Important Date:
    Paper Submission Deadline: 30th March 2024
    Notification of Acceptance: 30th April 2024
    Final Paper Submission: 30th May 2024
    Special Session Date: TBA

    Medical image analysis is a crucial aspect of modern healthcare, providing vital information for diagnosis, treatment planning, and patient monitoring. The integration of Artificial Intelligence (AI), particularly deep learning, has shown tremendous potential in enhancing the accuracy, efficiency, and effectiveness of medical image analysis. This special session aims to delve into the state-of-the-art deep learning techniques, applications, and methodologies specifically applied in the domain of medical image analysis. We are bringing together a diverse group of researchers, medical practitioners, AI experts, and academics to discuss, share, and collaborate on the latest advancements and challenges in the field.

    Topics of interest include, but are not limited to:
    - Advanced models and algorithms for medical image analysis
    - Natural language processing for clinical reports
    - Explainable AI in medical image analysis
    - Transfer learning in medical imaging
    - Generalizable representation learning in medical imaging
    - Segment anything model for medical image
    - Generative model in medical imaging
    - Ethical considerations and responsible AI in healthcare

    Baiying Lei, School of Biomedical Engineering, Shenzhen University, Shenzhen, China (leiby@szu.edu.cn)
    Dinghan Hu, Institute of Information and Control, Hangzhou Dianzi University, China (hdh@hdu.edu.cn)

  • For any inquiries or additional information, please contact the session organizers at leiby@szu.edu.cn

    Session on " Artificial Intelligence in Medical Image Analysis " will provide a valuable opportunity for the research community to collaborate and advance the state of the art in this dynamic and evolving field.