- Resume: Click here to download Xin Liu's resume.
- Education:
- PhD candidate, Illinois Institute of Technology, 2007-Present
- MS in Electrical Engineering, Illinois Institute of Technology, Chicago,2006
- MS in Electrical Engineering, Univerisity of Electronic Science and Technology of China, China, 2006
- BS,in Electrical Engineering, Univerisity of Electronic Science and Technology of China, China, 2003
- Research Interests:
Xin Liu's research interests are image processing, pattern recognition, filter, data estimation.
Please see the research link for more information.
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- Publications:
- Journal Papers:
[2] | Xin Liu, Deanna L. Langer, Masoom A. Haider, Yongyi Yang, Miles N. Wernick, Imam Samil Yetik
"Prostate Cancer Segmentation with Simultaneous Estimation of Markov Random Field Parameters and Class", IEEE Transactions on Medical
Imaging, vo. 28, no. 6, pp.906-915, 2009. |
[1] | Sedat Ozer, Deanna L. Langer, Xin Liu, Masoom A. Haider, Theodorus H. van der
Kwast, Andrew J. Evans, Yongyi Yang, Miles N. Wernick, Imam Samil Yetik, "Supervised and Unsupervised Methods for
Prostate Cancer Localization with Multispectral MRI", Medical Physics, pp.
1873-1883, 2010. |
- Conference Papers:
[5] | X. Liu, I. S. Yetik, "A Maximum Likelihood Classification
Method for Image Segmentation Considering Subject Variability," to appear, IEEE Southwest
Symposium on Image Analysis and Interpretation, 2010.
| [4] | X. Liu, M. A. Haider, D. L. Langer, I. S. Yetik, "Using Relatvie Contrast and Iterative Normalization
for Improved Prostate Cancer Localization with Multispectral MRI", ISBI 2010, pp. 1369-1372, 2010. |
[3] | Xin Liu, D. L. Langer, M. A. Haider, et al. "Unsupervised Segmentation of the Prostate Using MR
Images Based on Level Set with a Shape Prior", EMBS 2009, pp. 3613-3616, 2009. |
[2] | Xin Liu, Imam Samil Yetik, Miles N. Wernick, "Simultaneous Estimation of the Markov Random Field Parameters and the Classes for Image Segmentation", ICIP 2008, pp. 3048-3051,2008. |
[1] | Xin Liu, Y. Yang, Z. He, "A Combination Method for Medical Image Segmentation", Beijing Area Academic Symposium on Information and Communication Technology 2006. |
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