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161.
Waibel, D.J.E. ; Tiemann, U.* ; Lupperger, V. ; Semb, H.* & Marr, C.: In-silico staining from bright-field and fluorescent images using deep learning. In:. 2019. 184-186 (Lect. Notes Comput. Sc. ; 11729 LNCS)
162.
Gutiérrez-Becker, B.* et al.: Deep shape analysis on abdominal organs for diabetes prediction. Lect. Notes Comput. Sc. 11167 LNCS, 223-231 (2018)
163.
Klinger, E. & Hasenauer, J.: A scheme for adaptive selection of population sizes in approximate Bayesian Computation - Sequential Monte Carlo. Lect. Notes Comput. Sc. 10545 LNBI, 128-144 (2017)
164.
Bortsova, G. et al.: Mitosis detection in intestinal crypt images with hough forest and conditional random fields. Lect. Notes Comput. Sc. 10019, 287-295 (2016)
165.
Loos, C. ; Fiedler, A. & Hasenauer, J.: Parameter estimation for reaction rate equation constrained mixture models.  Lect. Notes Comput. Sc. 9859, 186-200 (2016)
166.
Zhou, L.* ; Georgii, E. ; Plant, C.* & Böhm, C.*: Covariate-related structure extraction from paired data. Lect. Notes Comput. Sc. 9832, 151-162 (2016)
167.
Bergmann, R.* & Weinmann, A.: Inpainting of cycling data using first and second order differences. Lect. Notes Comput. Sc. 8932, 155-168 (2015)
168.
Derntl, A. et al.: Stroke lesion segmentation using a probabilistic atlas of cerebral vascular territories. Lect. Notes Comput. Sc. (2015)
169.
Ilmonen, P.* ; Nordhausen, K.* ; Oja, H.* & Theis, F.J.: An affine equivariant robust second-order BSS method. Lect. Notes Comput. Sc. 9237, 328-335 (2015)
170.
Loos, C. ; Marr, C. ; Theis, F.J. & Hasenauer, J.: Approximate bayesian computation for stochastic single-cell time-lapse data using multivariate test statistics. Lect. Notes Comput. Sc. 9308, 52-63 (2015)
171.
Peter, L.* et al.: Leveraging random forests for interactive exploration of large histological images. Lect. Notes Comput. Sc. 8673, 1-8 (2015)
172.
Peter, L.* ; Pauly, O. ; Chatelain, P.* ; Mateus, D. & Navab, N.*: Scale-adaptive forest training via an efficient feature sampling scheme. Lect. Notes Comput. Sc. 9349, 637-644 (2015)
173.
Schröder, K.: Error estimates for approximate operator inversion via Kernel-based methods. Lect. Notes Comput. Sc. 9213, 399-413 (2015)
174.
Zweng, M.* et al.: Automatic guide-wire detection for neurointerventions using low-rank sparse matrix decomposition and denoising. Lect. Notes Comput. Sc. 9365, 114-123 (2015)
175.
Ceruto, T.* et al.: Mining medical data to obtain fuzzy predicates. Lect. Notes Comput. Sc. 8649, 103-117 (2014)
176.
Fröhlich, F. ; Theis, F.J. & Hasenauer, J.: Uncertainty analysis for non-identifiable dynamical systems: Profile likelihoods, bootstrapping and more. Lect. Notes Comput. Sc. 8859, 61-72 (2014)
177.
Fröhlich, F. ; Hross, S. ; Theis, F.J. & Hasenauer, J.: Radial basis function approximations of Bayesian parameter posterior densities for uncertainty analysis. Lect. Notes Comput. Sc. 8859, 73-85 (2014)
178.
Goebl, S.* ; Meyer-Baese, A.C.* ; Lobbes, M.B.I.* & Plant, C.: Segmentation and kinetic analysis of breast lesions in DCE-MR imaging using ICA. Lect. Notes Comput. Sc. 8649, 45-59 (2014)
179.
Hennersperger, C.* ; Mateus, D. ; Baust, M.* & Navab, N.A.*: A quadratic energy minimization framework for signal loss estimation from arbitrarily sampled ultrasound data. Lect. Notes Comput. Sc. 8674, 373-380 (2014)
180.
Khakhutskyy, V.* et al.: Centroid clustering of cellular lineage trees. Lect. Notes Comput. Sc. 8649, 15-29 (2014)
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