The Catholic University of America

Lin-Ching Chang, D.Sc.

Associate Professor
Electrical Engineering & Computer Science
Pangborn 311
202-319-4691 phone
202-319-5195 fax
changl@cua.edu

Education
D.Sc., Computer Science, George Washington University, Washington DC, 1998
M.Sc., Computer Science, George Washington University, Washington DC, 1993
B.Sc., Information and Computer Engineering, Chung-Yuan Christian University, Taiwan, 1991

Biography
Lin-Ching Chang's research interests include medical informatics, modeling and simulation, pattern recognition, data mining, combinatorial design, parallel processing, and telecommunication applications. During her career at the National Institutes of Health (NIH), she worked on several computational neuroscience projects focusing on algorithm design and software development for medical image processing and quantitative diffusion tensor magnetic resonance imaging (DTI) analysis. She was associated with the NIH pediatric neuroimaging project, a study to learn the brain development in normal healthy children and adolescents using MRI techniques. Prior to NIH, she was a senior software engineer at 3Com Corporation and worked on several commercial telecommunication projects including 3Com's unified messaging system, data encryption, and database systems migration. She also led several wireless applications projects including an interactive voice response system and short message service.

Selected Publications
1. L Dao, B Lucotte, B Glancy, L-C Chang, L-Y Hsu, R S Balaban Use of Independent Component Analysis to Improve Signal-to-noise Ratio in Multi-probe Fluorescence Microscopy. Journal of Microscopy, doi: 10.1111/jmi.12167, 2014.


2. L-C Chang, E El-Araby, V Dang, L Dao, GPU Acceleration of Nonlinear Diffusion Tensor Estimation Using CUDA and MPI, Neurocomputing 135: 328–338, 2014.


3. L-C Chang, L Walker L, C Pierpaoli, Informed RESTORE: A Method for Robust Estimation of Diffusion Tensor from Low Redundancy Datasets in the Presence of Physiological Noise Artifacts, Magnetic Resonance in Medicine 68:1654-1663, 2012.


4. S Rashidian, L-C Chang, P Asadollahi, Application of Statistical Pattern Recognition in a Solid-Fluid Interaction Problem, The Electronic Journal of Geotechnical Engineering Vol 16(N):1629-1637, 2011.


5. L Walker, L-C Chang, N Sharma, L Cohen, R Verma, C Pierpaoli, Effects of Physiological Noise in Population Analysis of Diffusion Tensor MRI data, NeuroImage 54(2):1168-77, 2011.


6. L-C Chang, CG Koay, PJ Basser, C Pierpaoli, A Linear Least Squares Method for Unbiased Estimation of T1 from SPGR Signals, Magnetic Resonance in Medicine 60:496–501, 2008.


7. CG Koay, U Nevo, L-C Chang, C Pierpaoli, PJ Basser, The Elliptical Cone of Uncertainty and Its Normalized Measures in Diffusion Tensor Imaging. IEEE Transaction on Medical Imaging 27(6): 834-846, 2008.


8. M Wu, L-C Chang, L Walker, H Lemaitre, AS Barnett, S Marenco, and Pierpaoli C, Comparison of EPI Distortion Correction Methods in Diffusion Tensor MRI Using a Novel Framework. Medical Image Computing and Computer Assisted Interventio, Part II, LNCS 5242, 321-329, 2008.


9. RZ Freidlin RZ, E Özarslan, ME Komlosh, L-C Chang, CG Koay, DK Jones, PJ Basser, Parsimonious Model Selection for Tissue Segmentation and Classification Applications: A Study Using Simulated and Experimental DTI data. IEEE Transaction on Medical Imaging 26(11): 1576-1584, 2007.


10. CG Koay, L-C Chang, C Pierpaoli, PJ Basser, Error Propagation Framework for Diffusion Tensor Imaging via Diffusion Tensor Representations. IEEE Transaction on Medical Imaging 26(8):1017-1034, 2007.


11. L-C Chang, CG Koay, C Pierpaoli, PJ Basser PJ, The Variance of DTI-derived Parameters via First-Order Perturbation Methods. Magnetic Resonance in Medicine 57:141-149, 2007.


12. CG Koay, L-C Chang, C Pierpaoli C, PJ Basser, A Unifying Theoretical and Algorithm Framework for Least Square Methods of Estimation in Diffusion Tensor Imaging. Journal of Magnetic Resonance 182:115-125, 2006.


13. Y Assaf, L Ben-Sira, S Constantini, L-C Chang, L Beni-Adani, Diffusion Tensor Imaging in Hydrocephalus: Initial Experience. AJNR Am J Neuroradiol 27:1717-1724, 2006.


14. L-C Chang, DK Jones, C Pierpaoli C, RESTORE: Robust Estimation of Tensors by Outlier Rejection. Magnetic Resonance in Medicine 53:1088-95, 2005.
 

Website
http://eecs.cua.edu/Research/CompInfomatics/index.cfm