材料化学工程国家重点实验室

学术报告

时间：2014年7月4日（星期五）上午9:30 – 10:30

地点：科技创新大楼A506报告厅

题目：Computational Medicine: Problems, Solutions, and Research Trends

      计算机科学在医学中应用：问题，手段和发展趋势

报告人：Prof. Danny Ziyi Chen, Fellow of IEEE（美国电气工程学会院士）

 Department of Computer Science and Engineering

 University of Notre Dame， USA

Computer technology plays a vital role in modern medicine and life sciences, especially in diagnostic imaging, human genome study, medical surgery and therapy, and medical data management.  As computing technology continues to evolve, computer science research and development will inevitably become an important part of modern medicine.  However, despite a great deal of research efforts, many key computational problems in the medical field are still not well understood.  Active participation of computer science researchers in formulating and solving core medical problems is urgently needed.  Since computational problems in modern medicine have direct impacts on the quality of life, the development of high quality computational solutions for medical problems is extremely crucial.

In this talk, we discuss a set of important computational problems and solutions in medical research and applications.  We first highlight several key computational problems in medical imaging and radiation cancer treatment, show how to formulate them as algorithmic problems and provide effective solutions for solving these problems.  We also discuss a number of computational problems that arise in emerging medical research and clinical practice, including cell identification and cell distribution analysis (in diagnosis and prognosis of breast cancer and auto-immune diseases, and in stem cell study of leukemiabone marrow micro-environments), segmentation of many different medical objects (e.g., blood clots, joint structures, retinal layers, airway and vascular networks, etc), motion tracking of massive swarming bacteria, radiation dose calculation, etc.  Examples of many-core parallel algorithms are given for some medical problems that require an enormous amount of computation.  Besides, we show experimental data and results to illustrate the clinical applications of our approaches.  Finally, we outline some possible future research trends of this emerging area.

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