Publications

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Filters: Author is B. Michael Kelm  [Clear All Filters]
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B
Kelm, B Michael, Müller, N, Menze, B H and Hamprecht, F A (2006). Bayesian Estimation of Smooth Parameter Maps for Dynamic Contrast-Enhanced MR Images with Block-ICM. Proc Computer Vision and Pattern Recognition Workshop (Mathematical Methods in Biomedical Image Analysis). IEEE Computer Society. 96-103PDF icon Technical Report (232.69 KB)
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Zechmann, C M, Kelm, B Michael, Zamecnik, P, Ikinger, U, Waldherr, R, Röll, S, Delorme, S, Hamprecht, F A and Bachert, P (2006). Can man still beat the machine? Automated vs. manual pattern recognition of 3D MRSI data of prostate cancer patients. Proceedings of the 16th ISMRMPDF icon Technical Report (664.38 KB)
Kelm, B Michael, Menze, B H, Neff, T, Zechmann, C M and Hamprecht, F A (2006). CLARET: a tool for fully automated evaluation of MRSI with pattern recognition methods.. Bildverarbeitung für die Medizin 2006 - Algorithmen, Systeme, Anwendungen. Springer. 51-55. http://www.efmi-wg-mip.net/service/bvm2006PDF icon Technical Report (275.25 KB)
Kaster, F O, Kelm, B Michael, Zechmann, C M, Weber, M - A, Hamprecht, F A and Nix, O (2009). Classification of Spectroscopic Images in the DIROlab Environment. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany. Springer. 25/V 252--255PDF icon Technical Report (145.73 KB)
Carlsohn, M F, Menze, B H, Kelm, B Michael, Hamprecht, F A, Kercek, A, Leitner, R and Polder, G (2006). Color image processing. CRC Press. 7(17) 393-419
Kelm, B Michael, Pal, C and McCallum, A (2006). Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning.. ICPR 2006. 2 828-832PDF icon Technical Report (114.99 KB)
Weber, C, Zechmann, C M, Kelm, B Michael, Zamecnik, R, Hendricks, D, Waldherr, R, Hamprecht, F A, Delorme, S, Bachert, P and Ikinger, U (2007). Comparison of correctness of manuel and automatic evaluation of MR-spectrum with prostrate cancer. Der Urologe. 46 1252
Menze, B H, Kelm, B Michael, Masuch, R, Himmelreich, U, Bachert, P, Petrich, W and Hamprecht, F A (2009). A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data. BMC Bioinformatics. 10:213PDF icon Technical Report (675 KB)
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Menze, B H, Kelm, B Michael, Splitthoff, N, Köthe, U and Hamprecht, F A (2011). On oblique random forests. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings. Springer. 453-469PDF icon Technical Report (665.33 KB)
Menze, B H, Lichy, M P, Bachert, P, Kelm, B Michael, Schlemmer, H P and Hamprecht, F A (2006). Optimal Classification of Long Echo Time in vivo Magnetic Resonance Spectra in the Detection of Recurrent Brain Tumor. NMR in Biomedicine. 19 599-609PDF icon Technical Report (289.77 KB)