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M
Monroy, A, Kröger, T, Arnold, M and Ommer, B (2011). Parametric Object Detection for Iconographic Analysis. Scientific Computing & Cultural Heritage. http://www.academia.edu/9439693/Parametric_Object_Detection_for_Iconographic_Analysis
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Lou, X, Fiaschi, L, Köthe, U and Hamprecht, F A (2012). Quality Classification of Microscopic Imagery with Weakly Supervised Learning. MICCAI-MLMI. Proceedings. 176-183PDF icon Technical Report (4.15 MB)
Lou, X (2011). Biomedical Data Analysis with Prior Knowledge: Modeling and Learning. University of Heidelberg
Lindner, M (2011). A Machine Learning Approach To Improve Digital Embryo Analysis. University of Heidelberg
Lichy, M P, Bachert, P, Hamprecht, F A, Weber, M - A, Debus, J, Schulz-Ertner, D, Kauczor, H - U and Schlemmer, H - P (2006). Einsatz der 1H-MR-spektroskopischen Bildgebung in der Strahlentherapie: Cholin als Marker für die Bestimmung der relativen Wahrscheinlichkeit eines Tumorprogresses nach Bestrahlung glialer Hirntumoren. Zeitung für Röntgenforschung. 178 627-633
Lerch, K (2006). Discontinuity Preserving Filtering Of Spectral Images. University of Heidelberg
Lenzen, F and Berger, J (2015). Solution-Driven Adaptive Total Variation Regularization. LNCS. Springer International Publishing. http://dx.doi.org/10.1007/978-3-319-18461-6_17PDF icon Technical Report (857.29 KB)
K
Künsch, H R, Agrell, E and Hamprecht, F A (2005). Optimal lattices for sampling. IEEE Transactions on Information Theory. 51 634-647
Kröger, T, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2014). Asymmetric Cuts: Joint Image Labeling and Partitioning. Pattern Recognition - 36th German Conference, {GCPR} 2014, Münster, Germany, September 2-5, 2014, Proceedings. http://dx.doi.org/10.1007/978-3-319-11752-2_16PDF icon Technical Report (3.46 MB)
Kröger, T, Mikula, S, Denk, W, Köthe, U and Hamprecht, F A (2013). Learning to Segment Neurons with Non-local Quality Measures. MICCAI 2013. Proceedings, part II. Springer. 8150 419-427PDF icon Technical Report (2.87 MB)
Kröger, (2010). Exploratory And Computational Analysis Of Huge Volume Images For Connectomics. University of Heidelberg
Kröger, (2014). Learning-based Segmentation for Connectomics. University of Heidelberg
Kreshuk, A, Walecki, R, Köthe, U, Gierthmühlen, M, Plachta, D, Genoud, C, Haastert-Talini, K and Hamprecht, F A (2015). Automated Tracing of Myelinated Axons and Detection of the Nodes of Ranvier in Serial Images of Peripheral Nerves. Journal of Microscopy. 259 (2) 143-154
Kreshuk, A, Straehle, C N, Sommer, C, Köthe, U, Cantoni, M, Knott, G W and Hamprecht, F A (2011). Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images. PLoS ONE. 6 (10)PDF icon Technical Report (290.48 KB)
Kreshuk, A, Straehle, C N, Sommer, C, Köthe, U, Knott, G W and Hamprecht, F A (2011). Automated Segmentation of Synapses in 3D EM Data. Eighth IEEE International Symposium on Biomedical Imaging (ISBI 2011). Proceedings. 220-223
Kreshuk, A, Stankiewicz, M, Lou, X, Kirchner, M, Hamprecht, F A and Mayer, M P (2010). Automated detection and analysis of bimodal isotope peak distribution in H/D exchange mass spectrometry using HeXicon. International Journal of Mass Spectrometry. 302 125-131PDF icon Technical Report (3.22 MB)
Kreshuk, A, Funke, J, Cardona, A and Hamprecht, F A (2015). Who is talking to whom: synaptic partner detection in anisotropic volumes of insect brain. MICCAI. Proceedings. Springer. LNCS 9349 661-668PDF icon Technical Report (2.14 MB)
Krasowski, N, Beier, T, Knott, G W, Köthe, U, Hamprecht, F A and Kreshuk, A (2015). Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors. 12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015. 536-539PDF icon Technical Report (2.25 MB)
Köthe, U, Andres, B, Kröger, T and Hamprecht, F A (2010). Geometric Analysis of 3D Electron Microscopy Data. Proceedings of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM). 22-26PDF icon Technical Report (1.43 MB)
Köthe, (2008). What Can We Learn from Discrete Images about the Continuous World. Discrete Geometry for Computer Imagery. Springer. 4992 4-19
Köthe, U, Herrmannsdörfer, F, Kats, I and Hamprecht, F A (2014). SimpleSTORM: a fast, self-calibrating reconstruction algorithm for localization microscopy. Histochemistry and Cell Biology. 141 613-627PDF icon Technical Report (2.29 MB)
König, (2007). Quality Control In Mass Spectrometry. University of Heidelberg
König, T, Menze, B H, Kirchner, M, Monigatti, F, Parker, K C, Patterson, T, Steen, J J, Hamprecht, F A and Steen, H (2008). Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics. Journal of Proteome Research. 7 3708-3717PDF icon Technical Report (1.16 MB)
Kleesiek, J, Biller, A, Urban, G, Köthe, U, Bendszus, M and Hamprecht, F A (2014). ilastik for Multi-modal Brain Tumor Segmentation. MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace. 12-17PDF icon Technical Report (405.91 KB)
Kirchner, M, Steen, J A J, Hamprecht, F A and Steen, H (2010). MGFp: An Open Mascot Generic Format Parser Library Implementation. Journal of Proteome Research. 9 (5) 27622763PDF icon Technical Report (125.18 KB)
Kirchner, M, Saussen, B, Steen, H, Steen, J A J and Hamprecht, F A (2007). amsrpm: Robust Point Matching in Retention Time Alignment of LC/MS Data with R. Journal of Statistical Software. 18 1-12. http://www.jstatsoft.org/v18/i04/paper
Kirchner, M, Renard, B Y, Köthe, U, Pappin, D J, Hamprecht, F A, Steen, J A J and Steen, H (2010). Computational Protein Profile Similarity Screening for Quantitative Mass Spectrometry Experiments. Bioinformatics. 26 (1) 77-83PDF icon Technical Report (380.19 KB)
Kirchner, M (2004). Spatial Extensions To Self-Modeling Curve Resolution. University of Heidelberg
Kirchner, M (2008). Analysis of Spectral Data. University of Heidelberg
Keränen, S V E, DePace, A, Hendriks, C L Luengo, Fowlkes, C, Arbelaez, P, Ommer, B, Brox, T, Henriquez, C, Wunderlich, Z, Eckenrode, K, Fischer, B, Hammonds, A and Celniker, S E (2009). Computational Analysis of Quantitative Changes in Gene Expression and Embryo Morphology between Species. Evolution-The Molecular Landscape
Kelm, B Michael (2007). Evaluation of Vector-Valued Clinical Image Data Using Probabilistic Graphical Models: Quantification and Pattern Recognition. University of HeidelbergPDF icon Technical Report (4.89 MB)
Kelm, B Michael, Kaster, F O, Henning, A, Weber, M - A, Bachert, P, Bösinger, P, Hamprecht, F A and Menze, B H (2011). Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images. NMR in Biomedicine. 25(1) 1-13PDF icon Technical Report (1.94 MB)
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)
Kelm, B Michael, Menze, B H, Zechmann, C M, Baudendistel, K T and Hamprecht, F A (2007). Automated Estimation of Tumor Probability in Prostate MRSI: Pattern Recognition vs. Quantification. Magnetic Resonance in Medicine. 57 150-159PDF icon Technical Report (348.05 KB)
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)

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