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Journal Publications 2014

  1. Baddeley, A.J., Coeurjolly, J.F., Rubak, E. & Waagepetersen, R. (2014): A logistic regression estimating function for Gibbs point processes. Biometrika 101, 377-392.
  2. Chen, C., Nielsen, M., Karssemeijer, N. & Brandt, S.S. (2014): Breast tissue segmentation from x-ray radiographs. Phys. Med. Biol. 59, 2445-2456.
  3. Cheplygina, V., Loog, M., Tax, D. & Feragen, A. (2014): Network-guided group feature selection for classification of autism spectrum disorder. MICCAI Workshop on Machine Learning for Medical Imaging. Lecture Notes in Computer Science 8679, 190-197. Springer.
  4. Coeurjolly, J.-F. & Møller, J. (2014): Variational approach for spatial point process intensity estimation. Bernoulli 20, 1097-1125.
  5. Deng, C., Waagepetersen, R. & Guan, Y. (2014): A combined estimating function approach for fitting stationary point process models. Biometrika 101, 393-408.
  6. Feragen, A., Nielsen, M., Jensen, E.B.V., du Plessis, A. & Lauze, F.B. (2014): Geometry and statistics: manifolds and stratified spaces. J. Math. Imaging Vis. 50, 1-4.
  7. Greilich, S., Hahn, U., Kiderlen, M., Andersen, C.E. & Bassler, N. (2014): Efficient calculation of local dose distributions for response modeling in proton and heavier ion beams. Eur. Phys. J. D 68, 327.
  8. Hauberg, S., Feragen, A. & Black, M.J. (2014): Grassmann averages for scalable robust PCA. Conference on Computer Vision and Pattern Recognition (CVPR), 2014 IEEE, 3810–3817.
  9. Huang, H., Ma, X., Waagepetersen, R., Holford, T., Wang, R., Risch, H., Mueller, L. & Guan, Y. (2014): A new estimation approach for combining epidemiological data from multiple sources. J. Am. Stat. Assoc. 109, 11-23.
  10. Jensen, E.B.V. & Ziegel, J.F. (2014): Local stereology of tensors of convex bodies. Methodol. Comput. Appl. Prob. 16, 263-282.
  11. Karemore, G., Nielsen, M., Karssemeijer, N. & Brandt, S.S. (2014): A method to determine the mammographic regions that show early changes due to the development of breast cancer. Phys. Med. Biol. 59, 6759-6773.
  12. Khanmohammadi, M., Waagepetersen, R.P., Nava, N., Nyengaard, J.R. & Sporring, J. (2014): Analysing the distribution of synaptic vesicles using a spatial point process model. Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 73-78.
  13. Lin, T.-Y., Voronovsky, A., Raabe, M., Urlaub, H., Sander, B. & Golas, M.M. (2014): Dual tagging as an approach to isolate endogenous chromatin remodeling complexes from Saccharomyces cerevisiae. BBA Proteins and Proteomics 1854, 198-208.
  14. Møller, J. & Toftager, H. (2014): Geometric anisotropic spatial point pattern analysis and Cox processes. Scand. J. Stat. 41, 414-435.
  15. Nava, N., Chen, F., Wegener, G., Popoli, M. & Nyengaard, J.R. (2014): A new efficient method for synaptic vesicle quantification reveals differences between medial prefrontal cortex perforated and nonperforated synapses. J. Comp. Neurol. 522, 284-297.
  16. Nava, N., Treccani, G., Liebenberg, N., Chen, F., Popoli, M., Wegener, G. & Nyengaard, J.R. (2014): Chronic desipramine prevents acute stress-induced reorganization of medial prefrontal cortex architecture by blocking glutamate vesicle accumulation and excitatory synapse increase. Int. J. Neuropsychoph. 18, 1-11.
  17. Pai, A., Sommer, S., Darkner, S., Sørensen, L., Sporring, J. & Nielsen, M. (2014): Stepwise inverse consistent Euler’s scheme for diffeomorphic image registration. Biomedical image registration: 6th International Workshop. Lecture Notes in Computer Science 8545, 223-230.
  18. Petersen, J., Nielsen, M., Lo, P., Nordenmark, L.H., Pedersen, J.H., Wille, M.M., Dirksen, A. & de Bruijne, M. (2014): Optimal surface segmentation using flow lines to quantify airway abnormalities in chronic obstructive pulmonary disease. Med. Image Anal. 18, 531-541.
  19. Petersen, J., Wille, M.M.W., Rakêt, L.L., Feragen, A., Pedersen, J.H., Nielsen, M., Dirksen, A. & de Bruijne, M. (2014): Effect of inspiration on airway dimensions measured in maximal inspiration CT images of subjects without airflow limitation. Eur. Radiol. 24, 2319-2325.
  20. Puelles, V., Douglas-Denton, R.N., Cullen-McEwen, L., McNamara, B.J., Salih, F., Li, J., Hughson, M.D., Hoy, W.E., Nyengaard, J.R. & Bertram, J.F. (2014): Design-based stereological methods for estimating numbers of glomerular podocytes. Ann. Anat. 196, 48-56.
  21. Rai, J., Pemmasani, J.K., Voronovsky, A., Jensen, I.S., Manavalan, A., Nyengaard, J.R., Golas, M.M. & Sander, B. (2014): Strep-tag II and Twin-Strep based cassettes for protein tagging by homologous recombination and characterization of endogenous macromolecular assemblies in Saccharomyces cerevisiae. Mol. Biotechnol. 56, 992-1003.
  22. Rakêt, L.L., Sommer, S.H. & Markussen, B. (2014): A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data. Pattern Recogn. Lett. 38, 1-7.
  23. Sabers, A., Bertelsen, F.C.B., Scheel-Krüger, J., Nyengaard, J.R & Møller, A. (2014): Long-term valproic acid exposure increases the number of neocortical neurons in the developing rat brain. A possible new animal model of autism. Neurosci. Lett. 580, 12-16.
  24. Schober, M., Kasenburg, N., Feragen, A., Hennig, P. & Hauberg, S. (2014): Probabilistic shortest path tractography in DTI using Gaussian Process ODE solvers. Medical Image Computing and Computer Assisted Intervention (MICCAI). Lecture Notes in Computer Science 8675, 265-272. Springer.
  25. Sommer, S.H., Lauze, F.B. & Nielsen, M. (2014): Optimization over geodesics for exact principal geodesic analysis. Adv. Comput. Math. 40, 283-313.
  26. Sporring, J., Khanmohammadi, M., Darkner, S., Nava, N., Nyengaard, J.R. & Jensen, E.B.V. (2014): Estimating the thickness of ultra thin sections for electron microscopy by image statistics. Proceedings of the 2014 IEEE International Symposium on Biomedical Imaging, Beijing, 29 April – 2 May 2014, 157-160.
  27. Svane, A.M. (2014a): On multigrid convergence of local algorithms for intrinsic volumes. J. Math. Imaging Vis. 49, 148-172.
  28. Svane, A.M. (2014b): Estimation of intrinsic volumes from digital grey-scale images. J. Math. Imaging Vis. 49, 352-376.
  29. Svane, A.M. (2014c): Local digital estimators of intrinsic volumes for Boolean models and in the design-based setting. Adv. Appl. Probab. 46, 35-58.
  30. Thórisdóttir, Ó. & Kiderlen, M. (2014): The invariator principle in convex geometry. Adv. Appl. Math. 58, 63-87.
  31. Thórisdóttir, Ó., Rafati, A.H. & Kiderlen, M. (2014): Estimating the surface area of non-convex particles from central planar sections. J. Microsc. 255, 49-64.
  32. Treccani, G., Musazzi, L., Perego, C., Milanese, M., Nava, N., Bonifacino, T., Lamanna, J., Malgaroli, A., Drago, F., Racagni, G., Nyengaard, J.R., Wegener, G., Bonanno, G. & Popoli, M. (2014): Stress and corticosterone increase the readily releasable pool of glutamate vesicles in synaptic terminals of prefrontal and frontal cortex. Mol. Psychiatr. 19, 433-443.
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Revised 03.06.2016