Symposium on Computational Modeling and Image Processing of Biomedical Problems

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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.