Mads Nielsen
Professor
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1, 2100 København Ø
- 2016
- Published
Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study
Winkel, R. R., von Euler-Chelpin, My Catarina, Nielsen, Mads, Petersen, P. K., Lillholm, Martin, Nielsen, Michael Bachmann, Lynge, Elsebeth, Uldall, W. Y. & Vejborg, I. M. M., 2016, In: B M C Cancer. 16, 12 p., 414.Research output: Contribution to journal › Journal article › peer-review
- Published
Supervised hub-detection for brain connectivity
Kasenburg, N., Liptrot, M. G., Reislev, N. L., Garde, Ellen, Nielsen, Mads & Feragen, A., 2016, Medical Imaging 2016: Image Processing. Styner, M. A. & Angelini, E. D. (eds.). SPIE - International Society for Optical Engineering, 9 p. 978409. (Progress in Biomedical Optics and Imaging; No. 39, Vol. 17).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Training shortest-path tractography: automatic learning of spatial priors
Kasenburg, N., Liptrot, M. G., Reislev, N. L., Ørting, Silas Nyboe, Nielsen, Mads, Garde, E. & Feragen, A., 2016, In: NeuroImage. 130, p. 63-76 14 p.Research output: Contribution to journal › Journal article › peer-review
- Published
Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring
Kallenberg, M. G. J., Petersen, P. K., Nielsen, Mads, Ng, A. Y., Diao, P., Igel, Christian, Vachon, C. M., Holland, K., Winkel, R. R., Karssemeijer, N. & Lillholm, Martin, 2016, In: IEEE Transactions on Medical Imaging. 35, 5, p. 1322-1331 10 p.Research output: Contribution to journal › Journal article › peer-review
- 2015
- Published
Adaptive time-stepping in dieomorphic image registration with bounded inverse consistency error
Pai, A. S. U., Klein, S., Sommer, Stefan Horst, Sørensen, L., Darkner, Sune, Sporring, Jon & Nielsen, Mads, 2015, Proceedings of the fifth international workshop on Mathematical Foundations of Computational Anatomy (MFCA 2015) . INRIA, p. 35-47Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Adaptive time-stepping in diffeomorphic image registration with bounded inverse consistency error
Pai, A. S. U., Klein, S., Sommer, Stefan Horst, Sørensen, L. E. B. L., Darkner, Sune, Sporring, Jon & Nielsen, Mads, 2015, The 18th International Conference on Medical Image Computing and Computer Assisted Intervention: proceedings. Technische Universität München , p. 35-47 13 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Assessing breast cancer masking risk in full field digital mammography with automated texture analysis
Kallenberg, M. G. J., Lillholm, Martin, Diao, P., Holland, K., Karssemeijer, N., Igel, Christian & Nielsen, Mads, 2015, 7th International Workshop on Breast Densitometry and Cancer Risk Assessment (Non-CME). University of California, p. 109 1 p.Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review
- Published
Assessing breast cancer masking risk with automated texture analysis in full field digital mammography
Kallenberg, M. G. J., Lillholm, Martin, Diao, P., Petersen, K., Holland, K., Karssemeijer, N., Igel, Christian & Nielsen, Mads, 2015, Breast Imaging and Interventional. Radiological Society of North America, Inc, p. 218 1 p.Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review
- Published
Automated texture scoring for assessing breast cancer masking risk in full field digital mammography
Kallenberg, M. G. J., Petersen, P. K., Lillholm, Martin, Jørgensen, D. R., Diao, P., Holland, K., Karssemeijer, N., Igel, Christian & Nielsen, Mads, 2015, In: Insights into Imaging. 6, 1, Supplement, 1 p., B-0212.Research output: Contribution to journal › Conference abstract in journal › peer-review
- Published
Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative
Dam, Erik Bjørnager, Lillholm, Martin, Marques, J. & Nielsen, Mads, 2015, In: SPIE Journal of Medical Imaging. 2, 2, 13 p., 024001.Research output: Contribution to journal › Journal article › peer-review
ID: 542361
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Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI
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Smoothing images creates corners
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Distribution, size, shape, growth potential and extent of abdominal aortic calcified deposits predict mortality in postmenopausal women
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