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Publications with keyword "Brain"

1. H. Jiang, P. Cao, M. Xu, J. Yang, O. Zaiane. "Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction ". Computers in Biology and Medicine, 127, December 2020. view
2. F. Aminmansour, A. Patterson, L. Le, Y. Pen, D. Mitchell, F. Pestilli, C. Caiafa, R. Greiner, M. White. "Learning Macroscopic Brain Connectomes via Group-Sparse Factorization". Neural Information Processing Systems (NIPS), (ed: H. Wallach, H. Larochelle, A. Beygelzimer, F. de-Buc, E. Fox, R. Garnett), pp 8847-8857, December 2019. view
3. M. Uhlich, R. Greiner, B. Hoehn, M. Woghiren, I. Diaz, T. Ivanova, A. Murtha. "Improved Brain Tumor Segmentation via Registration-Based Brain ". Forecasting, 1(1), pp 59-69, September 2018. view
4. M. Gheiratmand, I. Rish, G. Cecchi, M. Brown, R. Greiner, P. Bashivan, A. Greenshaw, R. Ramasubbu, S. Dursun. "Learning stable and predictive network-based patterns of schizophrenia and its clinical symptoms". Nature Schizophrenia, 3, pp 22, May 2017. PDFview
5. R. Ramasubbu, M. Brown, F. Cortese, I. Gaxiola, A. Greenshaw, S. Dursun, B. Goodyear, R. Greiner. "Accuracy of Automated Classification of Major Depressive Disorder as a Function of Symptom Severity". NeuroImage: Clinical, 12, pp 320-331, July 2016. PDFview
6. I. Diaz, P. Boulanger, R. Greiner, B. Hoehn, L. Rowe, A. Murtha. "An Automatic Brain Tumor Segmentation Tool". Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp 3339-3342, July 2013. view
7. M. Ben Salah, I. Diaz, R. Greiner, P. Boulanger, B. Hoehn, A. Murtha. "Fully Automated Brain Tumor Segmentation Using Two MRI Modalities". International Symposium on Visual Computing, pp 30-39, July 2013. view
8. I. Diaz, P. Boulanger, R. Greiner, A. Murtha. "A critical review of the effects of de-noising algorithms on MRI brain tumor segmentation". IEEE Engineering in Medicine and Biology Society Conference, September 2011. view
9. B. Saha, N. Ray, R. Greiner, A. Murtha, H. Zhang. "Quick Detection of Brain Tumors and Edemas: A Bounding Box Method Using Symmetry". Computerized Medical Imaging and Graphics, August 2011. view
10. P. Mosayebi. "Tumor Invasion Margin from Diffusion Weighted Imaging". MSc Thesis, University of Alberta, February 2010. PDFview
11. A. Farhangfar, R. Greiner, C. Szepesvari. " Learning to Segment from a Few Well-Selected Training Images". International Conference on Machine Learning (ICML), June 2009. PDFview
12. C. Lee, S. Wang, M. Brown, A. Murtha, R. Greiner. "Segmenting Brain Tumors using Pseudo-Conditional Random Fields". Medical Image Computing and Computer-Assisted Intervention, pp 359-366, September 2008. PDFview
13. C. Lee, M. Brown, S. Wang, A. Murtha, R. Greiner. "Constrained Classification on Structured Data". National Conference on Artificial Intelligence (AAAI), July 2008. PDFview
14. I. Levner, H. Zhang, R. Greiner. "Heterogeneous Stacking for Classification Driven Watershed Segmentation". EURASIP Journal on Advances in Signal Processing, 2008(Article ID 485821 (9 pages)), January 2008. view
15. N. Ray, R. Greiner, A. Murtha. "Using Symmetry to Detect Abnormalities in Brain MRI". Computer Society of India Communications, 31(19), pp 7--10, January 2008. PDFview
16. A. Murtha, J. Levesque, M. Brown, M. Heydari, J. Sander, M. Jagersand, N. Leong, W. Roa, B. Abdulkarim, D. Fulton, M. Smerdely, R. Greiner. "Development of an image-centered database containing MRI and PET data, and examples of its application in the treatment of glioma patients". Canadian Association of Radiation Oncology, June 2007. view
17. C. Lee, S. Wang, F. Jiao, D. Schuurmans, R. Greiner. "Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields". Neural Information Processing Systems (NIPS), December 2006. PDFview
18. M. Morris, R. Greiner, J. Sander, A. Murtha, M. Schmidt. "Learning a Classification-based Glioma Growth Model Using MRI Data". Journal of Computers (JCP), 1(7), pp 21-31, November 2006. PDFview
19. M. Morris, R. Greiner, J. Sander, A. Murtha, M. Schmidt. "A Classification-based Glioma Diffusion Model Using MRI Data". Canadian Conference on Artificial Intelligence (CAI), Quebec City, May 2006. PDFview
20. M. Schmidt, I. Levner, R. Greiner, A. Murtha, A. Bistritz. "Segmenting Brain Tumors using Alignment-Based Features". International Conference on Machine Learning and Applications (ICMLA), Los Angeles, December 2005. PDFview
21. M. Schmidt. "Automatic Brain Tumor Segmentation". MSc Thesis, Dept of Computing Science, University of Alberta, November 2005. PDFview
22. C. Lee, M. Schmidt, A. Murtha, A. Bistritz, J. Sander, R. Greiner. "Segmenting Brain Tumor with Conditional Random Fields and Support Vector Machines". Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends, Springer, (ed: Liu, Yanxi; Jiang, Tianzi; Zhang, Changshui), pp 469-478, October 2005. PDFview
23. C. Lee, R. Greiner, M. Schmidt. "Support Vector Random Fields for Spatial Classification". European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), Porto, Portugal, pp 121-132, October 2005. PDFview
24. R. Sutton. "Machines That Learn and Mimic the Brain". ACCESS, GTE's Journal of Science and Technology, January 1992. view
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