Biomedical Engineering Reference
In-Depth Information
15. M.J. Baemani, A. Monadjemi, P. Moallem, Detection of respiratory abnormalities using
artificial neural networks. J Comput. Sci. 4(8), 663-667 (2008)
16. S. Jafari, H. Arabalibeik, K. Agin, Classification of normal and abnormal respiration patterns
using flow volume curve and neural network, in International Symposium on Health
Informatics and Bioinformatics, pp. 110-113, 2010
17. I. Ayappa, R.G. Norman, D. Whiting, A.H.W. Tsai, F. Anderson, E. Donnely, D.J.
Silberstein, D.M. Rapoport, Irregular respiration as a marker of wakefulness during titration
of CPAP. Sleep 32(1), 99-104 (2009)
18. T. Mu, T.C. Pataky, A.H. Findlow, M.S.H. Aung, J.Y. Goulermas, Automated nonlinear
feature generation and classification of foot pressure lesions. IEEE Trans. Inf Technol.
Biomed. 14(2), 418-424 (2010)
19. H. Atoui, J. Fayn, P. Rubel, A novel neural-network model for deriving standard 12-lead ecgs
from serial three-lead ECGS: application to self-care. IEEE Trans. Inf Technol. Biomed.
14(3), 883-890 (2010)
20. P. Chazal, M. O'Dwyer, R.B. Reilly, Automatic classification of heartbeats using ECG
morphology and heartbeat interval features. IEEE Trans. Biomed. Eng. 51(7), 1196-1206
(2004)
21. P. Chazal, R.B. Reilly, A patient-adapting heartbeat classifier using ECG morphology and
heartbeat interval features. IEEE Trans. Biomed. Eng. 53(12), 2535-2543 (2006)
22. C.I. Christodoulou, C.S. Pattichis, M. Pantziaris, A. Nicolaides, Texture-based classification
of atherosclerotic carotid plaques. IEEE Trans. Med. Imag. 22(7), 902-912 (2003)
23. W. Chen, C.E. Metz, M.L. Giger, K. Drukker, A novel hybrid linear/nonlinear classifier for
two-class classification: Theory, algorithm, and applications. IEEE Trans. Med. Imag. 29(2),
428-441 (2010)
24. A.H. Khandoker, J. Gubbi, M. Palaniswami, Automated scoring of obstructive sleep apnea
and
hypopnea
events
using
short-term
electrocardiogram
recordings.
IEEE
Trans.
Inf
Technol. Biomed. 13(6), 1057-1067 (2009)
25. M. Hoogeman, J.B. Prévost, J. Nuyttens, J. Pöll, P. Levendag, B. Heijmen, Clinical accuracy
of the respiratory tumor tracking system of the cyberknife: Assessment by analysis of log
files. Int. J. Radiat. Oncol. Biol. Phys. 74(1), 297-303 (2009)
26. S.J. Lee, Y. Motai, M. Murphy, Respiratory motion estimation with hybrid implementation of
extended Kalman filter. IEEE Trans. Ind. Electron. 59(11), 4421-4432 (2012)
27. W. Bai, S.M. Brady, Motion correction and attenuation correction for respiratory gated PET
images. IEEE Trans. Med. Imag. 30(2), 351-365 (2011)
28. J. Ehrhardt, R. Werner, A. Schmidt-Richberg, H. Handels, Statistical modeling of 4D
respiratory lung motion using diffeomorphic image registration. IEEE Trans. Med. Imag.
30(2), 251-265 (2011)
29. A.P. King, K.S. Rhode, R.S. Razavi, T.R. Schaeffter, An adaptive and predictive respiratory
motion model for image-guided interventions: theory and first clinical application. IEEE
Trans. Med. Imag. 28(12), 2020-2032 (2009)
30. A. Lanatà, E.P. Scilingo, E. Nardini, G. Loriga, R. Paradiso, D. De-Rossi, Comparative
evaluation of susceptibility to motion artifact in different wearable systems for monitoring
respiratory rate. IEEE Trans. Inf Technol. Biomed. 14(2), 378-386 (2010)
31. F. Pernkopf, D. Bouchaffra, Genetic-based EM algorithm for learning Gaussian mixture
models. IEEE Trans. Pattern Anal. Mach. Intell. 27(8), 1344-1348 (2005)
32. P. Guo, P. Guo, M.R. Lyu, Cluster number selection for a small set of samples using the
bayesian Ying-Yang model. IEEE Trans. Neural Netw. 13(3), 757-763 (2002)
33. J. Zhao, P.L.H. Yu, Fast ML estimation for the mixture of factor analyzers via an ECM
algorithm. IEEE Trans. Neural Netw. 19(11), 1956-1961 (2008)
34. V. Chandola, A. Banerjee, V. Kumar, Anomaly detection: A survey. ACM Comput. Surv.
41(3), 5:1-15:58 (2009)
35. M.A. Kupinski, D.C. Edwards, M.L. Giger, C.E. Metz, Ideal observer approximation using
bayesian classification neural networks. IEEE Trans. Med. Imag. 20(9), 886-899 (2001)
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