Mads Nielsen

Mads Nielsen

Professor

ORCID: 0000-0003-1535-068X

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  1. Published

    Breast tissue segmentation and mammographic risk scoring using deep learning

    Petersen, P. K., Nielsen, Mads, Diao, P., Karssemeijer, N. & Lillholm, Martin, 2014, Breast imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings. Fujita, H., Hara, T. & Muramatsu, C. (eds.). Springer Science+Business Media, p. 88-94 7 p. (Lecture notes in computer science, Vol. 8539).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  2. Published

    Breast tissue segmentation from x-ray radiographs

    Chen, C., Nielsen, Mads, Karssemeijer, N. & Brandt, S. S., 2014, In: Physics in Medicine and Biology. 59, 10, p. 2445-2456 12 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  3. Published

    Brownian Warps for Non-Rigid Registration

    Nielsen, Mads, Johansen, P., Jackson, Andrew D., Lautrup, B. E. & Hauberg, S., 2008, In: Journal of Mathematical Imaging and Vision. 31, 2-3, p. 221-231 11 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  4. Brownian Warps: A least committed prior for non-rigid registration

    Nielsen, Mads, Johansen, P., Lautrup, B. & Jackson, A. D., 2002, Medical Image Computing and Computer-Assisted Intervention — MICCAI: 5th International Conference Tokyo, Japan, September 25–28, 2002 Proceedings, Part II. Springer, p. 557-564 (Lecture notes in computer science, Vol. 2489/2002).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  5. Published

    CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data

    Mehdipour Ghazi, Mostafa, Sørensen, L., Ourselin, S. & Nielsen, Mads, 2021, arXiv.org, 11 p.

    Research output: Working paper › Preprint

  6. Published

    CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning From Sporadic Temporal Data

    Mehdipour Ghazi, Mostafa, Sørensen, L., Ourselin, S. & Nielsen, Mads, 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 1, p. 792-802

    Research output: Contribution to journal › Journal article › Research › peer-review

  7. Published

    COVID-19-associated cerebral microbleeds in the general population

    Sagar, M. V., Ferrer, N. R., Mehdipour Ghazi, Mostafa, Klein, Kiril Vadimovic, Solem, Espen Victor Jimenez, Nielsen, Mads & Kruuse, Christina Rostrup, 2024, In: Brain Communications. 6, 3, fcae127.

    Research output: Contribution to journal › Journal article › Research › peer-review

  8. Cartilage curvature

    Dam, E. B., Folkesson, J., Petterson, P., Olsen, O. F., Nielsen, Mads & Christiansen, C., 1 Sep 2006

    Research output: Patent

  9. Published

    Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage

    Prasoon, A., Igel, Christian, Loog, M., Lauze, Francois Bernard, Dam, E. & Nielsen, Mads, 2012, Medical Imaging 2012: Image Processing. Haynor, D. R. & Ourselin, S. (eds.). SPIE - International Society for Optical Engineering, Vol. 8314. 9 p. 83144V. (SPIE Proceedings, Vol. 8314).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  10. Published

    Change in mammographic density across birth cohorts of Dutch breast cancer screening participants

    Napolitano, George, Lynge, Elsebeth, Lillholm, Martin, Vejborg, I. M. M., van Gils, C. H., Nielsen, Mads & Karssemeijer, N., 2019, In: International Journal of Cancer. 145, 11, p. 2954-2962 9 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  11. Published

    Characterization of errors in deep learning-based brain MRI segmentation

    Pai, A. S. U., Teng, Y., Blair, J. P. M., Kallenberg, M. G. J., Dam, Erik Bjørnager, Sommer, Stefan Horst, Igel, Christian & Nielsen, Mads, 2017, Deep learning for medical image analysis. Zhou, S. K., Greenspan, H. & Shen, D. (eds.). Academic Press, p. 223–242 20 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  12. Published

    Chronic Obstructive Pulmonary Disease Quantification Using CT Texture Analysis and Densitometry: Results From the Danish Lung Cancer Screening Trial

    Sørensen, L., Nielsen, Mads, Petersen, Jens, Pedersen, J. H., Dirksen, A. & de Bruijne, Marleen, 2020, In: American Journal of Roentgenology. 214, 6, p. 1269-1279

    Research output: Contribution to journal › Journal article › Research › peer-review

  13. Published

    Classification in medical image analysis using adaptive metric k-NN

    Chen, C., Chernoff, K., Karemore, G., Lo, P. C. P., Nielsen, Mads & Lauze, Francois Bernard, 2010, Medical Imaging 2010: image processing. Dawant, B. M. & Haynor, D. R. (eds.). SPIE - International Society for Optical Engineering, 9 p. 76230S. (Progress in Biomedical Optics and Imaging; No. 33, Vol. 11).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  14. Published

    Classification of Laser Induced Fluorescence Spectra from Normal and Malignant bladder tissues using Learning Vector Quantization Neural Network in Bladder Cancer Diagnosis

    Karemore, G. R., Mascarenhas, K. K., Patil, C., V.K, U., Prabhu, V., Chowla, A., Nielsen, Mads & C, S., 2008, BIBE 2008: 8th. IEEE International Conference on Bioinformatics and BioEngineering, 8-10 October 2008. IEEE Communications Society, p. 1-6 6 p.

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  15. Published

    Classification of protein profiles using fuzzy clustering techniques: an application in early diagnosis of oral, cervical and ovarian cancer

    Karemore, G., Mullick, J. B., Sujatha, R., Nielsen, Mads & Santhosh, C., 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, p. 6361-6364 4 p. (I E E E Engineering in Medicine and Biology Society. Conference Proceedings).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  16. Published

    Combining different views of mammographic texture resemblance (MTR) marker of breast cancer risk

    Sun, S., Karemore, G., Chernoff, K., Karssemeijer, N. & Nielsen, Mads, 2011. 2 p.

    Research output: Contribution to conference › Conference abstract for conference › Research › peer-review

  17. Published

    Combining the boundary shift integral and tensor-based morphometry for brain atrophy estimation

    Michalkiewicz, M. D., Pai, A. S. U., Leung, K. K., Sommer, Stefan Horst, Darkner, Sune, Sørensen, L., Sporring, Jon & Nielsen, Mads, 2016, Medical imaging 2016: Image processing. Styner, M. A. & Angelini, E. D. (eds.). SPIE - International Society for Optical Engineering, 6 p. 978406. (Progress in Biomedical Optics and Imaging).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  18. Published

    Comparative analysis of multimodal biomarkers for amyloid-beta positivity detection in Alzheimer's disease cohorts

    Mehdipour Ghazi, Mostafa, Selnes, P., Timón-Reina, S., Tecelão, S., Ingala, S., Bjørnerud, A., Kirsebom, B. E., Fladby, T. & Nielsen, Mads, 2024, In: Frontiers in Aging Neuroscience. 16, 1345417.

    Research output: Contribution to journal › Journal article › Research › peer-review

  19. Published

    Comparison of several computational pipelines for atrophy computation in longitudinal Alzheimers studies

    Pai, A. S. U., Sommer, Stefan Horst, Darkner, Sune, Sørensen, L. E. B. L., Sporring, Jon & Nielsen, Mads, 2015. 1 p.

    Research output: Contribution to conference › Conference abstract for conference › Research › peer-review

  20. Computer Vision - ECCV 2002: 7th European Conference on Computer Vision Copenhagen, Denmark, May 28–31, 2002 Proceedings, Part II

    Heyden, A. (ed.), Sparr, G. (ed.), Nielsen, Mads (ed.) & Johansen, P. (ed.), 2002, <Forlag uden navn>. (Lecture notes in computer science, Vol. 2351/2002).

    Research output: Book/Report › Book › Research › peer-review

  21. Computer Vision - ECCV 2002: 7th European Conference on Computer Vision Copenhagen, Denmark, May 28–31, 2002 Proceedings, Part IV

    Heyden, A. (ed.), Sparr, G. (ed.), Nielsen, Mads (ed.) & Johansen, P. (ed.), 2002, <Forlag uden navn>. (Lecture notes in computer science, Vol. 2353/2002).

    Research output: Book/Report › Book › Research › peer-review

  22. Computer Vision - ECCV 2002: 7th European Conference on Computer Vision Copenhagen, Denmark, May 28–31, 2002 Proceedings, Part III

    Heyden, A. (ed.), Sparr, G. (ed.), Nielsen, Mads (ed.) & Johansen, P. (ed.), 2002, <Forlag uden navn>. (Lecture notes in computer science, Vol. 2352/2002).

    Research output: Book/Report › Book › Research › peer-review

  23. Computer Vision - ECCV 2002: 7th European Conference on Computer Vision Copenhagen, Denmark, May 28–31, 2002 Proceedings, Part I

    Heyden, A. (ed.), Sparr, G. (ed.), Nielsen, Mads (ed.) & Johansen, P. (ed.), 2002, Denmark. (Lecture notes in computer science, Vol. 2350/2002).

    Research output: Book/Report › Book › Research › peer-review

  24. Published

    Computer analysis method for analyzing images involves applying algorithm to aligned images to extract quantitative estimate of difference in volume of object shown in second image by calculating change in volume of object

    Pai, A. S. U., Sørensen, L., Dam, E., Lillholm, Martin & Nielsen, Mads, 2014, IPC No. A61B-005/00, Patent No. US2014357978-A1, 4 Dec 2014, Priority date 4 Jun 2013, Priority No. US909666

    Research output: Patent

  25. Published

    Computer based method for determining the size of an objects in an image

    Pai, A. S. U., Sørensen, L., Dam, E. B., Lillholm, Martin & Nielsen, Mads, 4 Dec 2014, Priority date 4 Dec 2014

    Research output: Patent

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