Image analysis – Applications – Biomedical applications
Reexamination Certificate
2007-07-12
2011-11-22
Ahmed, Samir (Department: 2624)
Image analysis
Applications
Biomedical applications
Reexamination Certificate
active
08064662
ABSTRACT:
A method for modeling an image for multiple tasks includes providing an image with n image features, providing an indicator matrix which has m non-zero components corresponding to m selected features selected from the n image features, constructing a model of the image using the in selected features for each specific labeling task. There is a variable for a specific task to be performed on the image and a variable for a plurality of tasks to be performed on the image.
REFERENCES:
patent: 5062066 (1991-10-01), Scher et al.
patent: 5800179 (1998-09-01), Bailey
patent: 2002/0028021 (2002-03-01), Foote et al.
patent: 2003/0058268 (2003-03-01), Loui et al.
Ando, R. K., and Zhang, T. 2005. A framework for learning predictive structures from multiple tasks and unlabeled data.Journal of Machine Learning Research6:1855-1887.
Argyriou, A.; Evgeniou, T.; and Pontil, M. 2007. Multitask feature learning. In Scholkopf, B.; Platt, J.; and Hoffman, T., eds.,Advances in Neural Information Processing Systems 19. Cambridge, MA: MIT Press.
Bi, J.; Bennett, K.; Embrechts, M.; Breneman, C.; and Song, M. 2003. Dimensionality reduction via sparse support vector machines.Journal of Machine Learning Research3:1229-1243.
Buchbinder, S.; Leichter, I.; Lederman, R.; Novak, B.; Bamberger, P.; Sklair-Levy, M.; Yarmish, G.; and Fields, S. 2004. Computer-aided classification of BI-RADS category 3 breast lesions.Radiology230:820-823.
Evegniou, T., and Pontil, M. 2004. Regularized multi-task learning. InProc. of 17-th SIGKDD Conf. on Knowledge Discovery and Data Mining.
Heskes, T. 2000. Empirical bayes for learning to learn. In Langley, P., ed.,Proceedings of the 17th International Conference on Machine Learning, 367-374.
Weston, J.; Elisseeff, A.; Scholkopf, B.; and Tipping. M. 2003. Use of the zero-norm with linear models and kernel methods.Journal of Machine Learning Research3:1439-1461.
Zhu, J.; Rosset, S.; Hastie, T.; and Tibshirani. R. 2004. 1-norm support vector machines. In Thrun, S.; Saul, L.; and Scholkopf, B., eds.,Advances in Neural Information Processing Systems 16. Cambridge, MA: MIT Press.
Ahmed Samir
Fitzpatrick Atiba
Siemens Medical Solutions USA , Inc.
Withstandley Peter
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