Symposium on Computational Modeling and Image Processing of Biomedical Problems

生物医学问题计算建模与图像处理研讨会

• 批准号: 1931844
• 负责人: Zhengfu Xu
• 金额: $ 1.5万
• 依托单位: Michigan Technological University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931844&HistoricalAwards=false
• 关键词: Symposium; Computational; Modeling; Image; Processing

Title: Symposium on Computational Modeling and Image Processing of Biomedical ProblemsConference location: Michigan Technological University (MTU) Date: June 15-17, 2019Website: http://pages.mtu.edu/~zhengfux/Overview.htm. From the discovery of penicillin (1928) to Human Genome Project (1990), breakthroughs in medicine have greatly impacted billions of people on earth. Among them, developments of medical imaging techniques such as x-ray imaging, computed tomography (CT) scans, magnetic resonance imaging (MRI), and a variety of other radiological imaging techniques have allowed the examination of the internal condition of the body without the use of invasive surgical procedures. Furthermore, medical imaging technologies are being increasingly used to provide guidance for surgery, biopsy, and radiation therapy in real-time. We are now on the cusp of another breakthrough era, given the availability of data, computational power, and novel computing methodology such as artificial intelligence, thereby potentially elevating human healthcare to a level never seen before. Mathematics, particularly, computational and applied mathematics, plays a foundational role in the projected advancement. The primary focus of the proposed interdisciplinary symposium is to provide an update on recent important contributions to computational and numerical methods in biomedical problems. Applying novel mathematics and modeling techniques to extract new or additional information from complex bio-medical datasets are particularly encouraged. Topics of interest include mathematical and computing methods and their immediate applications in the following areas: a) Novel mathematical image formation/reconstruction/processing methods and their applications in biomedical problems; b)Novel mathematical algorithms enabling multi-scale and multi-physics simulation related to biomedical problems;c) Scientific visualization and analytics of (BIG) biomedical data; d) Novel machine learning and statistical analysis methods and their application in (BIG) biomedical data. One of the main challenges when integrating mathematics into biomedical sciences is overcoming existing barriers. Unfamiliarity with biomedical language, distinct disciplinary-bound approaches to research in the mathematics community, and 'artificial' academic boundaries aimed at 'preserving subject integrity' can hinder developments in this line of interdisciplinary research. The secondary objective of this symposium is to provide a platform so that intelligent exchanges among applied mathematicians, biomedical engineers, and clinical scientists can take place, fostering interdisciplinary collaborations. A concerted effort will be made to include underrepresented students and early and middle-career mathematicians in the symposium. Using existing resources available at the Michigan Technological University, the organizers will work together with the Center of Diversity and Inclusion and other partners to recruit students who are typically from economically-disadvantageous backgrounds to attend this symposium. In addition, it is planned to create a future network of support and interaction among participants to enable further research and collaboration.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

职务名称：生物医学问题的计算建模和图像处理研讨会会议地点：密歇根理工大学（MTU）日期：2019年6月15日至17日网站：http://pages.mtu.edu/~zhengfux/Overview.htm。从青霉素的发现（1928年）到人类基因组计划（1990年），医学的突破极大地影响了地球上数十亿人。其中，诸如X射线成像、计算机断层摄影（CT）扫描、磁共振成像（MRI）和各种其他放射成像技术的医学成像技术的发展已经允许在不使用侵入性外科手术的情况下检查身体的内部状况。此外，医学成像技术正越来越多地用于为手术、活检和放射治疗提供实时指导。我们现在正处于另一个突破性时代的风口浪尖上，考虑到数据的可用性，计算能力和人工智能等新的计算方法，从而有可能将人类医疗保健提升到前所未有的水平。数学，特别是计算和应用数学，在计划的进步中起着基础性的作用。拟议的跨学科研讨会的主要重点是提供一个更新的生物医学问题的计算和数值方法的最新重要贡献。特别鼓励应用新的数学和建模技术从复杂的生物医学数据集中提取新的或额外的信息。感兴趣的主题包括数学和计算方法及其在以下领域的直接应用：a）新的数学图像形成/重建/处理方法及其在生物医学问题中的应用; B）与生物医学问题相关的多尺度和多物理模拟的新数学算法;c）（BIG）生物医学数据的科学可视化和分析; d）新的机器学习和统计分析方法及其在（BIG）生物医学数据中的应用。将数学融入生物医学科学的主要挑战之一是克服现有的障碍。不熟悉生物医学语言，不同的学科约束的方法，在数学界的研究，和“人为的”学术界限，旨在“保持学科的完整性”，可以阻碍发展这条线的跨学科研究。本次研讨会的第二个目标是提供一个平台，使应用数学家，生物医学工程师和临床科学家之间的智能交流可以发生，促进跨学科合作。一个协调一致的努力将包括代表性不足的学生和早期和中期职业数学家在研讨会。利用密歇根理工大学现有的资源，组织者将与多样性和包容性中心和其他合作伙伴合作，招募通常来自经济不利背景的学生参加这次研讨会。此外，还计划在参与者之间建立一个未来的支持和互动网络，以实现进一步的研究和合作。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。