Books and Book Chapters

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  1. “Deep Learning Techniques on Texture Analysis of Chest and Breast Images”, Biomedical Texture Analysis, Elsevier, 2017. [Jie-Zhi Cheng, Chung-Ming Chen, Dinggang Shen]
  2. “Information Processing in Medical Imaging”, Lecture Notes in Computer Science (LNCS, volume 10265), Proceedings of IPMI 2017, Springer-Verlag, Berlin, 2017. [Marc Niethammer, Martin Styner, Stephen Aylward, Hongtu Zhu, Ipek Oguz, Pew-Thian Yap, Dinggang Shen]
  3. “Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching”, Deep Learning for Medical Image Analysis, Elsevier, 2016. [Yanrong Guo, Yaozong Gao, Dinggang Shen]
  4. “Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning”, Deep Learning for Medical Image Analysis, Elsevier, 2016. [Shaoyu Wang, Minjeong Kim, Guorong Wu, Dinggang Shen]
  5. "Deep Learning for Medical Image Analysis", Academic Press, 2016. [Kevin Zhou, Hayit Greenspan and Dinggang Shen]
  6. "Machine Learning and Medical Imaging", Academic Press, 2016. [Guorong Wu, Dinggang Shen, Mert Sabuncu]
  7. "Deep Learning in Diagnosis of Brain Disorders", Recent Progress in Brain and Cognitive Engineering, Volume 5 of the series Trends in Augmentation of Human Performance: 203-213, Springer, 2015 [Heung-Il Suk, Dinggang Shen]
  8. "Brain Functional Networks in the Developing Brain Using Resting BOLD", Advanced Brain Neuroimaging Topics in Health and Disease - Methods and Applications, InTech, 2014. [Wei Gao, Hongtu Zhu, Kelly S. Giovanello, J. Keith Smith, Dinggang Shen, John H. Gilmore and Weili Lin]
  9. Support Vector Machines for Neuroimage Analysis: Interpretation from Discrimination”, Support Vector Machines Applications, Springer, 2014. [Luping Zhou, Lei Wang, Lingqiao Liu, Philip Ogunbona, Dinggang Shen]
  10. "Machine Learning in Medical Imaging”, (Lecture Notes in Computer Science, vol.8184), Proceedings of MLMI2013, Springer-Verlag, Berlin, 2013. [Wu, G., Zhang, D., Shen, D., Yan, P., Suzuki, K., Wang, F. (Eds.)]
  11. "Multimodal Brain Image Analysis”, (Lecture Notes in Computer Science, vol.8159), Proceedings of MBIA2013, Springer-Verlag, Berlin, 2013. [Shen, L., Liu, T., Yap, P.-T., Huang, H., Shen, D., Westin, C.-F.  (Eds.)]
  12. "Machine Learning in Medical Imaging”, (Lecture Notes in Computer Science, vol.7588), Proceedings of MLMI2012, Springer-Verlag, Berlin, 2012. [Wang, F., Shen, D., Yan, P., Suzuki, K. (Eds.)]
  13. "Multimodal Brain Image Analysis”, (Lecture Notes in Computer Science, vol.7509), Proceedings of MBIA2012, Springer-Verlag, Berlin, 2012. [Yap, P.-T., Liu, T., Shen, D., Westin, C.-F., Shen, L.  (Eds.)]
  14. Brain Disease Classification and Progression Using Machine Learning Techniques", Computational Intelligence in Biomedical Imaging, Springer, 2012. [Bo Cheng, Chong-Yaw Wee, Manhua Liu, Daoqiang Zhang, and Dinggang Shen]
  15. Emergence of Groupwise Registration in MR Brain Study”, Biosignal Processing: Principles and Practices, CRC Press, 2012. [Guorong Wu, Hongjun Jia, Qian Wang, Feng Shi, Pew-Thian Yap, and Dinggang Shen]
  16. "Machine Learning in Medical Imaging”, (Lecture Notes in Computer Science, vol.7009), Proceedings of MLMI2011, Springer-Verlag, Berlin, 2011. [Suzuki, K., Wang, F., Shen, D., Yan, P. (Eds.)]
  17. "Multimodal Brain Image Analysis”, (Lecture Notes in Computer Science, vol.7012), Proceedings of MBIA2011, Springer-Verlag, Berlin, 2011. [Liu, T., Shen, D., IBANEZ, L., Tao, X. (Eds.)]
  18. "Machine Learning Techniques for AD/MCI Diagnosis and Prognosis," Machine Learning in Healthcare Informatics, Springer, 2011. [Chong-Yaw Wee, Daoqiang Zhang, Luping Zhou, Pew-Thian Yap, and Dinggang Shen]
  19. "Machine Learning in Medical Imaging”, (Lecture Notes in Computer Science, vol.6357), Proceedings of MLMI2010, Springer-Verlag, Berlin, 2010. [Wang, F., Yan, P., Suzuki, K., Shen, D. (Eds.)]
  20. Medical Imaging and Augmented Reality”, (Lecture Notes in Computer Science, vol.4091), Proceedings of MIAR2006, Springer-Verlag, Berlin, 2006. [Guang-Zhong Yang, Tianzi Jiang, Dinggang Shen, Lixu Gu, and Jie Yang (Eds.)]