You are here: CSGB Publications CSGB Journal Publications Journal Publications 2017

Journal Publications 2017

  1. Ardalan, M., Rafati, A.H., Nyengaard, J.R. & Wegener, G. (2017): Rapid antidepressant effect of ketamine correlates with astroglial plasticity in the hippocampus. Brit. J. Pharmacol. 174, 483-492.
  2. Arnaudon, A., Holm, D.D., Pai, A. & Sommer, S. (2017): A stochastic large deformation model for computational anatomy. Proceedings of the International Conference on Image Processing in Medical Imaging (IPMI 2017). Lecture Notes in Computer Science 10265, pp. 571-582. Springer.
  3. Coeurjolly, J.-F., Møller, J. & Waagepetersen, R. (2017a): A tutorial on Palm distributions for spatial point processes. Int. Stat. Rev. 85, 404-420.
  4. Coeurjolly, J.-F., Møller, J. & Waagepetersen, R. (2017b): Palm distributions for log Gaussian Cox processes. Scand. J. Stat. 44, 192–203.
  5. Deng, C., Guan, Y., Waagepetersen, R. & Zhang, J. (2017): Second-order quasi-likelihood for spatial point processes. Biometrics 73, 1311-1320.
  6. Greisen, S.R., Yan, Y., Hansen, A.S., Venø, M.T., Nyengaard, J.R., Moestrup, S.K., Hvid, M., Freeman, G.J., Kjems, J. & Deleuran, B. (2017): Extracellular vesicles transfer the receptor programmed death-1 in rheumatoid arthritis. Front Immunol. 8, 851.
  7. Hansen, J.D.K. & Lauze, F. (2017): Local mean multiphase segmentation with HMMF models. In Proceedings of the International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2017). Lecture Notes in Computer Science 10302, pp. 396-407.
  8. Hooghoudt, J.-O., Barroso, M. & Waagepetersen, R. (2017): Toward Bayesian inference of the spatial distribution of proteins from three-cube Förster resonance energy transfer data. Ann. Appl. Stat. 11, 1711-1737.
  9. Hug, D., Kiderlen, M. & Svane, A.M. (2017): Voronoi-based estimation of Minkowski tensors from finite point samples. Discrete Comput. Geom. 57, 545-570.
  10. Hörrmann, J. & Svane, A.M. (2017): Local digital algorithms applied to Boolean models. Scand. J. Stat. 44, 369-395.
  11. Jensen, E.B.V. & Kiderlen, M. (2017a, eds.): Tensor Valuations and their Applications in Stochastic Geometry and Imaging. Lecture Notes in Mathematics 2177. Springer.
  12. Jensen, E.B.V. & Kiderlen, M. (2017b): Rotation invariant valuations. In: Tensor Valuations and their Applications in Stochastic Geometry and Imaging (eds. E.B.V. Jensen and M. Kiderlen). Lecture Notes in Mathematics 2177, pp. 185-212. Springer.
  13. Khanmohammadi, M., Darkner, S., Nava, N., Nyengaard, J.R., Wegener, G., Popoli, M. & Sporring, J. (2017): 3D analysis of synaptic vesicle density and distribution after acute foot-shock stress by using serial section transmission electron microscopy. J. Microsc. 265, 101–110.
  14. Kiderlen, M. & Dorph-Petersen, K.-A. (2017): The Cavalieri estimator with unequal section spacing revisited. Image Anal. Stereol. 36, 133-139.
  15. Kousholt, A. (2017): Reconstruction of n-dimensional convex bodies from surface tensors. Adv. Appl. Math. 83, 115-144.
  16. Kousholt, A., Ziegel, J.F., Kiderlen, M. & Jensen, E.B.V. (2017): Stereological estimation of mean particle volume tensors in R3 from vertical sections. In: Tensor Valuations and their Applications in Stochastic Geometry and Imaging (eds. E.B.V. Jensen and M. Kiderlen). Lecture Notes in Mathematics 2177, pp. 423-434. Springer.
  17. Kühnel, L. & Sommer, S. (2017a): Computational anatomy in Theano. Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics. GRAIL 2017, MFCA 2017, MICGen 2017. Lecture Notes in Computer Science 10551, pp. 164-176. Springer.
  18. Kühnel, L. & Sommer, S. (2017b): Stochastic development regression on non-linear manifolds. Proceedings of the International Conference on Image Processing in Medical Imaging (IPMI 2017). Lecture Notes in Computer Science 10265, pp. 53-64. Springer.
  19. Kühnel, L., Sommer, S., Pai, A. & Raket, L.L. (2017): Most likely separation of intensity and warping effects in image registration. SIAM J. Imaging Sci. 10, 578-601.
  20. Lauze, F., Quéau, Y. & Plenge, E. (2017): Simultaneous reconstruction and segmentation of CT scans with shadowed data. In Proceedings of the International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2017). Lecture Notes in Computer Science 10302, pp. 308-319.
  21. Mallasto, A. & Feragen, A. (2017): Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes. Advances in Neural Information Processing Systems 30 (NIPS).
  22. Mrkvička, T., Myllymäki, M. & Hahn, U. (2017): Multiple Monte Carlo testing, with applications in spatial point processes. Stat. Comp. 27, 1239–1255.
  23. Myllymäki, M., Mrkvička, T., Grabarnik, P., Seijo, H. & Hahn, U. (2017): Global envelope tests for spatial processes. J. Roy. Stat. Soc. B 79, 381-404.
  24. Møller, J. & Waagepetersen, R. (2017): Some recent developments in statistics for spatial point patterns. Annual Review of Statistics and Its Applications 4, 317-342.
  25. Pai, A.S.U., Sommer, S.H., Raket, L.L., Kühnel, L., Darkner, S., Sørensen, L. & Nielsen, M. (2017): A statistical model for simultaneous template estimation, bias correction, and registration of 3D brain images. In Proceedings of MICCAI 2016. Lecture Notes in Computer Science 10081, pp. 151-159. Springer.
  26. Prokešová, M., Dvořák, J. and Jensen, E.B.V. (2017): Two-step estimation procedures for inhomogeneous shot-noise Cox processes. Ann. Inst. Statist. Math. 69, 513-542.
  27. Rønn-Nielsen, A. & Jensen, E.B.V. (2017): Excursion sets of infinitely divisible random fields with convolution equivalent Lévy measure. J. Appl. Prob. 54, 833-851.
  28. Rønn-Nielsen, A., Sporring, J. & Jensen, E.B.V. (2017): Estimation of sample spacing in stochastic processes. Image Anal. Stereol. 36, 43-49.
  29. Schaldemose, E.L., Fontain, F.I., Karlsson, P. & Nyengaard, J.R. (2017): Improved sampling and analysis of images in corneal confocal microscopy. J. Microsc. 268, 3-12.
  30. Sommer, S.H., Arnaudon, A., Kühnel, L. & Joshi, S. (2017): Bridge simulation and metric estimation on landmark manifolds. In Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics. GRAIL 2017, MFCA 2017, MICGen 2017. Lecture Notes in Computer Science 10551, pp. 79-91. Springer.
  31. Sommer, S.H. & Svane, A.M. (2017): Modelling anisotropic covariance using stochastic development and sub-Riemannian frame bundle geometry. J. Geom. Mech. 9, 391-410.
  32. Svane, A.M. (2017): Valuations in image analysis. In: Tensor Valuations and their Applications in Stochastic Geometry and Imaging (eds. E.B.V. Jensen and M. Kiderlen). Lecture Notes in Mathematics 2177, pp. 435-454. Springer.
  33. Svane, A.M. & Jensen, E.B.V. (2017): Rotational Crofton formulae for Minkowski tensors and some affine counterparts. Adv. Appl. Math. 91, 44-75.
  34. Sørensen, L., Igel, C., Pai, A.S.U., Balas, I., Anker, C., Lillholm, M. & Nielsen, M. (2017): Differential diagnosis of mild cognitive impairment and Alzheimer’s disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry. NeuroImage Clin. 13, 470-482.
Comments on content: 
CSGB static webpages

Revised 20.03.2018