Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
- 2018
- Published
The combined effect of mammographic texture and density on breast cancer risk: a cohort study
Wanders, J. O. P., van Gils, C. H., Karssemeijer, N., Holland, K., Kallenberg, M., Peeters, P. H. M., Nielsen, Mads & Lillholm, Martin, 2018, In: Breast Cancer Research. 20, 10 p., 36.Research output: Contribution to journal › Journal article › peer-review
- 2017
- Published
Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: a case control study
Winkel, R. R., von Euler-Chelpin, My Catarina, Lynge, Elsebeth, Diao, P., Lillholm, Martin, Kallenberg, M., Forman, Julie Lyng, Nielsen, Michael Bachmann, Uldall, W. Y., Nielsen, Mads & Vejborg, I. M. M., Aug 2017, In: Cancer Epidemiology. 49, p. 53-60 8 p.Research output: Contribution to journal › Journal article › peer-review
- Published
Differential diagnosis of mild cognitive impairment and Alzheimer’s disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry
Sørensen, L., Igel, Christian, Pai, A. S. U., Balas, I., Anker, C., Lillholm, Martin & Nielsen, Mads, 2017, In: NeuroImage: Clinical. 13, p. 470-482 13 p.Research output: Contribution to journal › Journal article › peer-review
- 2016
- Published
Deformation-based atrophy computation by surface propagation and its application to Alzheimer’s disease
Pai, A. S. U., Sporring, Jon, Darkner, Sune, Dam, Erik Bjørnager, Lillholm, Martin, Jørgensen, D., Oh, J., Chen, G., Suhy, J., Sørensen, L. & Nielsen, Mads, 2016, In: SPIE Journal of Medical Imaging. 3, 1, 11 p., 014005.Research output: Contribution to journal › Journal article › peer-review
- Published
Learning density independent texture features
Kallenberg, M. G. J., Nielsen, Mads, Holland, K., Karssemeijer, N., Igel, Christian & Lillholm, Martin, 2016, Breast Imaging: 13th International Workshop, IWDM 2016, Malmö, Sweden, June 19-22, 2016, Proceedings. Tingberg, A., Lång, K. & Timberg, P. (eds.). Springer, p. 299-306 8 p. (Lecture notes in computer science, Vol. 9699).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 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
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
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
ID: 152298477
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Mammographic texture resemblance generalizes as an independent risk factor for breast cancer
Research output: Contribution to journal › Journal article › peer-review
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624
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Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study
Research output: Contribution to journal › Journal article › peer-review
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338
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Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative
Research output: Contribution to journal › Journal article › peer-review
Published