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Publications about 'Challenge'
Articles in journal, book chapters
  1. Zhi Lu, Gustavo Carneiro, Andrew Bradley, Daniela Ushizima, Masoud Nosrati, Andrea Bianchi, Claudia Carneiro, and Ghassan Hamarneh. Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells. IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 00(00):00-00, 2016. Keyword(s): Challenge, Segmentation. [bibtex-key = jbhi2016]


  2. Urs Ribary, Alex L. Mackay, Alexander Rauscher, Christine M. Tipper, Debbie Giaschi, Todd S. Woodward, Vesna Sossi, Sam M. Doesburg, Lawrence M. Ward, Anthony Herdman, Ghassan Hamarneh, Brian G. Booth, and Alexander Moiseev. Emerging neuroimaging technologies: Towards future personalized diagnostics, prognosis, targeted intervention and ethical challenges. (Chapter 2). Neuroethics: Anticipating the Future, pp 00-00, 2016. ISBN: 9780198786832. Keyword(s): Diffusion MRI. [bibtex-key = neuroethics2016]


  3. Ching-Wei Wang, Cheng-Ta Huang, Meng-Che Hsieh, Chung-Hsing Li, Sheng-Wei Chang, Wei-Cheng Li, Remy Vandaele, Raphael Maree, Sebastien Jodogne, Pierre Geurts, Cheng Chen, Guoyan Zheng, Chengwen Chu, Hengameh Mirzaalian, Ghassan Hamarneh, Tomaz Vrtovec, and Bulat Ibragimov. Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge. IEEE Transactions on Medical Imaging (IEEE TMI), 34(9):1890-900, 2015. Keyword(s): Challenge, Graph based, Optimization, Machine Learning, Registration and Matching. [bibtex-key = tmi2015b]


Conference articles
  1. Hengameh Mirzaalian and Ghassan Hamarneh. Automatic Globally-Optimal Pictorial Structures with Random Decision Forest Based Likelihoods For Cephalometric X-Ray Landmark Detection. In Automatic Cephalometric X-Ray Landmark Detection Challenge 2014, in conjunction with IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pages 1-12, 2014. Keyword(s): Challenge, Machine Learning, Optimization. [bibtex-key = isbi2014_chlg_ceph]


  2. Masoud Nosrati and Ghassan Hamarneh. A Variational Approach for Overlapping Cell Segmentation. In Overlapping Cervical Cytology Image Segmentation Challenge, in conjunction with IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pages 1-2, 2014. Keyword(s): Challenge, Segmentation. [bibtex-key = isbi2014_chlg_cell]


Internal reports
  1. Jeremy Kawahara and Ghassan Hamarneh. Fully Convolutional Networks to Detect Clinical Dermoscopic Features. Technical report arXiv:1703.04559, March 2017. Keyword(s): Machine Learning, Deep Learning, Dermatology, Challenge. [bibtex-key = arXiv:1703.04559]



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Last modified: Wed Oct 18 00:00:28 2017
Author: hamarneh.


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