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U

B. Michael Kelm, Kaster, F. O., Henning, A., Weber, M. - A., Bachert, P., Bösinger, P., Hamprecht, F. A., and Menze, B. H., “Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images”, NMR in Biomedicine, vol. 25(1), pp. 1-13, 2011.

Technical Report (1.94 MB)

S

L. Görlitz, Menze, B. H., Weber, M. - A., and Kelm, B. Michael, “Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields”, in Pattern Recognition, 2007, vol. 4713, pp. 224-233.

Technical Report (872.46 KB)

P

L. Görlitz, Menze, B. H., Kelm, B. Michael, and Hamprecht, F. A., “Processing Spectral Data”, Surface and Interface Analysis, vol. 41, pp. 636-644, 2009.

Technical Report (4.17 MB)

O

B. H. Menze, Lichy, M. P., Bachert, P., Kelm, B. Michael, Schlemmer, H. P., and Hamprecht, F. A., “Optimal Classification of Long Echo Time in vivo Magnetic Resonance Spectra in the Detection of Recurrent Brain Tumor”, NMR in Biomedicine, vol. 19, pp. 599-609, 2006.

Technical Report (289.77 KB)

B. H. Menze, Kelm, B. Michael, Splitthoff, N., Köthe, U., and Hamprecht, F. A., “On oblique random forests”, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings., 2011, pp. 453-469.

Technical Report (665.33 KB)

M

B. H. Menze, Kelm, B. Michael, Weber, M. - A., Bachert, P., and Hamprecht, F. A., “Mimicking the human expert: pattern recognition for an automated assessment of data quality in MRSI”, Magnetic Resonance in Medicine, vol. 59, pp. 1457-1466, 2008.

Technical Report (1.45 MB)

B. H. Menze, Kelm, B. Michael, Heck, D., Lichy, M. P., and Hamprecht, F. A., “Machine-based rejection of low quality spectra and estimation of brain tumor probabilities from magnetic resonance spectroscopic images”, in Bildverarbeitung für die Medizin, 2006, pp. 31-36.

Technical Report (672.84 KB)

F

B. H. Menze, Kelm, B. Michael, and Hamprecht, F. A., “From eigenspots to fisherspots -- latent spaces in the nonlinear detection of spot patterns in a highly variable background”, in Advances in data analysis, 2007, vol. 33, pp. 255-262.

Technical Report (248.87 KB)

E

B. Michael Kelm, “Evaluation of Vector-Valued Clinical Image Data Using Probabilistic Graphical Models: Quantification and Pattern Recognition”. University of Heidelberg, 2007.

Technical Report (4.89 MB)

B. Michael Kelm, Menze, B. H., Nix, O., Zechmann, C. M., and Hamprecht, F. A., “Estimating Kinetic Parameter Maps from Dynamic Contrast-Enhanced MRI using Spatial Prior Knowledge”, IEEE Transaction on Medical Imaging, vol. 28:10, pp. 1534-1547, 2009.

Technical Report (419.8 KB)

C

B. H. Menze, Kelm, B. Michael, Masuch, R., Himmelreich, U., Bachert, P., Petrich, W., and Hamprecht, F. A., “A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data”, BMC Bioinformatics, vol. 10:213, 2009.

Technical Report (675 KB)

C. Weber, Zechmann, C. M., Kelm, B. Michael, Zamecnik, R., Hendricks, D., Waldherr, R., Hamprecht, F. A., Delorme, S., Bachert, P., and Ikinger, U., “Comparison of correctness of manuel and automatic evaluation of MR-spectrum with prostrate cancer”, Der Urologe, vol. 46, p. 1252, 2007.

B. Michael Kelm, Pal, C., and McCallum, A., “Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning.”, in ICPR 2006, 2006, vol. 2, pp. 828-832.

Technical Report (114.99 KB)

M. F. Carlsohn, Menze, B. H., Kelm, B. Michael, Hamprecht, F. A., Kercek, A., Leitner, R., and Polder, G., “Color image processing”, vol. 7(17), R. Lukac and Plataniotis, K. N., Eds. CRC Press, 2006, pp. 393-419.

F. O. Kaster, Kelm, B. Michael, Zechmann, C. M., Weber, M. - A., Hamprecht, F. A., and Nix, O., “Classification of Spectroscopic Images in the DIROlab Environment”, in World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2009, vol. 25/V, p. 252--255.

Technical Report (145.73 KB)

B. Michael Kelm, Menze, B. H., Neff, T., Zechmann, C. M., and Hamprecht, F. A., “CLARET: a tool for fully automated evaluation of MRSI with pattern recognition methods.”, in Bildverarbeitung für die Medizin 2006 - Algorithmen, Systeme, Anwendungen, 2006, pp. 51-55.

Technical Report (275.25 KB)

C. M. Zechmann, Kelm, B. Michael, Zamecnik, P., Ikinger, U., Waldherr, R., Röll, S., Delorme, S., Hamprecht, F. A., and Bachert, P., “Can man still beat the machine? Automated vs. manual pattern recognition of 3D MRSI data of prostate cancer patients”, in Proceedings of the 16th ISMRM, 2006.

Technical Report (664.38 KB)

B

B. Michael Kelm, Müller, N., Menze, B. H., and Hamprecht, F. A., “Bayesian Estimation of Smooth Parameter Maps for Dynamic Contrast-Enhanced MR Images with Block-ICM”, in Proc Computer Vision and Pattern Recognition Workshop (Mathematical Methods in Biomedical Image Analysis), 2006, pp. 96-103.

Technical Report (232.69 KB)

A

B. Michael Kelm, Menze, B. H., and Hamprecht, F. A., “Automatische Lokalisation von Tumoren in 1H-NMR-spektroskopischen in vivo Aufnahmen”, in VDI-Berichte, 2005, vol. 1883, pp. 457-466.

Technical Report (221.54 KB)

C. M. Zechmann, Menze, B. H., Kelm, B. Michael, Zamecnik, P., Ikinger, U., Waldherr, R., Delorme, S., Hamprecht, F. A., and Bachert, P., “Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer”, Academic Radiology, vol. 19, 6, pp. 675-684, 2012.

B. Michael Kelm, Menze, B. H., Zechmann, C. M., Baudendistel, K. T., and Hamprecht, F. A., “Automated Estimation of Tumor Probability in Prostate MRSI: Pattern Recognition vs. Quantification”, Magnetic Resonance in Medicine, vol. 57, pp. 150-159, 2007.

Technical Report (348.05 KB)