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. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
10. | P. Mosayebi. "Tumor Invasion Margin from Diffusion Weighted Imaging". MSc Thesis, University of Alberta, February 2010. |
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. |
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. |
13. | C. Lee, M. Brown, S. Wang, A. Murtha, R. Greiner. "Constrained Classification on Structured Data". National Conference on Artificial Intelligence (AAAI), July 2008. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
21. | M. Schmidt. "Automatic Brain Tumor Segmentation". MSc Thesis, Dept of Computing Science, University of Alberta, November 2005. |
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. |
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. |
24. | R. Sutton. "Machines That Learn and Mimic the Brain". ACCESS, GTE's Journal of Science and Technology, January 1992. |