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招收一两名访问学生参与中美合作科研项目（医学图像可视化和配准）
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欢迎同学（一到两名研究生）参与医学图像可视化和配准项目。该项目由即将在一月中旬到北大信息学院担任教职的袁晓如博士和明尼苏达大学磁共振中心的Greg Metzger博士合作开展。非北大学生参与将以访问学生的身份到北大参加科研。具体情况见附文。有兴趣的同学请尽快将简历用电子邮件发给袁晓如博士xiaoru[dot]yuan[at]gmail[dot]com. Recruiting Students for Medical Image Registration Project Center for Magnetic Resonance Research, University of Minnesota School of EECS, Peking University We are seeking one or two qualified students to work on a medical image visualization and registration project related to the prostate cancer research. The project will involve extending an existing software tool and developing new functions to: 1) Reconstruct a 3D volume from digitized prostate pathology slides and 2) Register the 3D pathology volume to magnetic resonance imaging (MRI) data acquired in vivo. This is a non-trivial task as the MRI data is acquired with a setup which locally distorts the prostate and the pathology slides are made from a removed and fixed prostate gland which also experiences changes in shape. The project has partially developed codes which can performance the reconstruction and registration of the 3D pathology data. The student(s) will develop new codes and algorithms towards a fully functionalized program. The successful applicant will have experience in both programming and image processing with the time and interest in applying their skills in the area of medical research. While not mandatory, practical knowledge of deformable registration methods would be helpful in accomplishing the goals of this project. The specific development environment is C/C++, VTK/ITK with Visual Studio .net. The student is expected to work at Peking University for a period of at least half year full time with Dr. Xiaoru Yuan (http://www.cs.umn.edu/~xyuan) at Peking Univ. and Dr. Greg Metzger at University of Minnesota jointly. Non-PKU student will be invited to Peking University as a visiting student. Interested parties please send your resume and a cover letter (in English or Chinese) to Dr. Xiaoru Yuan at xiaoru[dot]yuan[at]gmail[dot]com as soon as possible. Background Information: The full potential of magnetic resonance imaging to improve the diagnosis and management of prostate cancer has not yet been fully realized. MRI allows the noninvasive acquisition of three-dimensional (3D) anatomic, vascular and metabolic information. While MRI is currently being used clinically to aid in diagnosis and staging, it has the potential to provide the necessary information to target focal therapies and develop patient specific treatment strategies. However, in order to realize this potential, more rigorous validation studies must be undertaken to understand the best way to use the multi-parametric MRI to determine the extent (location and volume) of cancer and its aggressiveness. Pathology data acquired after the removal of the prostate is the best gold standard to use for validation purposes. Detailed analysis of pathology slides made from the removed prostate can be directly compared with MRI data acquired prior to surgery. However, before this comparison can be made, the interpreted pathology slides must be reconstructed back into a 3D volume and co-registered to the in vivo MRI data. The methods developed in this work will make it possible to use pathology results as a gold standard for training statistical classifiers based on the MRI data. It is envisioned that these classifiers will be able to generate 3D probability maps of cancer with the MRI data alone. The ability to generate these probability maps would have a tremendous impact on the management of prostate cancer. Bio: Dr. Xiaoru Yuan received the BS degree in chemistry and the BA degree in law from Peking University, China, in 1997 and 1998, respectively. He received the MS degree in computer engineering in 2005 and Ph.D Degree in computer science in 2006, both from the University of Minnesota at Twin Cities in 2005. He currently works at the Center of Magnetic Resonance Research (CMRR) at the University of Minnesota as a research associate. Starting from the middle of January 2008, he will join the School of Electronics Engineering and Computer Science at Peking University as a faculty member. Dr. Yuan's primary research interests fall in the field of visualization and computer graphics with emphasis on information visualization, high performance rendering and visualization for massive data sets, non-photorealistic rendering and its application in illustrative visualization, novel visualization user interface, and computational geometry. Dr. Yuan collaborates widely with scientists from various areas, including astronomy, geophysics, chemistry, biology, etc. He has authored or coauthored over 20 technical papers on prestigious international journals and conferences including IEEE Transactions on Visualization and Computer Graphics, and IEEE conference on visualization. His work on high dynamic range volume visualization received Best Paper Award at the IEEE Visualization 2005 conference. For more information, visit http://www.cs.umn.edu/~xyuan. [search]医学可视化[/search] |
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