Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
A category system on the shape index descriptor of local image structure induced by natural image statistics
Lillholm, Martin & Griffin, L. D., 2006, In: Perception. 35, Supplement, p. 48-49 2 p.Research output: Contribution to journal › Conference abstract in journal › Research
- Published
A novel OA efficacy marker: cartilage activity
Jørgensen, D. R., Lillholm, Martin & Dam, E. B., 2013, In: Osteoarthritis and Cartilage. 21, Supplement, p. S21-S22 2 p., 28.Research output: Contribution to journal › Conference abstract in journal › Research
- Published
Alzheimer's disease diagnostic performance of a multi-atlas hippocampal segmentation method using the harmonized hippocampal protocol
Anker, C., Sørensen, L., Pai, A. S. U., Lyksborg, M., Lillholm, Martin, Conradsen, K., Larsen, R. & Nielsen, Mads, 2014. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
- Published
An evaluation of a novel technique for fully automatic synovitis quantification from pre- and post-contrast wrist MRI
Mysling, P., Dam, E., Zaim, S., Genant, H., Fuerst, T. & Lillholm, Martin, 2012, In: Annals of the Rheumatic Diseases. 71, Supplement 3, p. 303-304 2 p., THU0439.Research output: Contribution to journal › Conference abstract in journal › 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 › Research › peer-review
- Published
Automatic measurement of wrist synovitis from contrast-enhanced MRI: a registration-centered approach
Mysling, P., Darkner, Sune, Sporring, Jon, Dam, E. & Lillholm, Martin, 2013, Medical Imaging 2013: Image Processing. Ourselin, S. & Haynor, D. R. (eds.). SPIE - International Society for Optical Engineering, 6 p. 86692U. (Progress in Biomedical Optics and Imaging; No. 36, Vol. 14).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Automatic segmentation of vertebrae from radiographs: a sample-driven active shape model approach
Mysling, P., Petersen, P. K., Nielsen, Mads & Lillholm, Martin, 2011, Machine Learning in Medical Imaging: Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011. Proceedings. Suzuki, K., Wang, F., Shen, D. & Yan, P. (eds.). Springer, p. 10-17 8 p. (Lecture notes in computer science, Vol. 7009).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Basic image features (BIFs) arising from approximate symmetry type
Griffin, L. D., Lillholm, Martin, Crosier, M. & van Sande, J., 2009, Scale Space and Variational Methods in Computer Vision: Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings. Tai, X-C., Mørken, K., Lysaker, M. & Lie, K-A. (eds.). Springer, p. 343-355 13 p. (Lecture notes in computer science, Vol. 5567).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › 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 › Research › peer-review
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628
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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
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339
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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 › Research › peer-review
Published