Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
ORCID: 0000-0002-1402-6899
1 - 5 out of 5Page size: 10
- 2011
- Published
Maximum a posteriori estimation of linear shape variation with application to vertebra and cartilage modeling
Crimi, A., Lillholm, Martin, Nielsen, Mads, Ghosh, A., de Bruijne, Marleen, Dam, E. B. & Sporring, Jon, 2011, In: IEEE Transactions on Medical Imaging. 30, 8, p. 1514-1526 13 p.Research output: Contribution to journal › Journal article › Research › peer-review
Method for analyzing magnetic resonance imaging (MRI) image of bone to identify e.g. osteoarthritis, involves combining features of textural information within region of interest (ROI) to estimate level of disease
Dam, E. B., Granlund, R. L. & Lillholm, Martin, 2011, IPC No. G06T-007/00, Patent No. WO2011151242-A1, 8 Dec 2011, Priority date 1 Jun 2010, Priority No. GB009101Research output: Patent
- Published
Finding discriminative regions that optimally separate healthy and osteoarthritis knees
Jørgensen, D. R., Lillholm, Martin & Dam, E. B., 2011, In: Osteoarthritis and Cartilage. 19, Supplement 1, p. S192 414.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
- Published
Vertebral fracture risk (VFR) score for fracture prediction in postmenopausal Women
Lillholm, Martin, Ghosh, A., Pettersen, P. C., de Bruijne, Marleen, Dam, E. B., Karsdal, M. A., Christiansen, C., Genant, H. K. & Nielsen, Mads, 2011, In: Osteoporosis International. 22, 7, p. 2119-2128 10 p.Research output: Contribution to journal › Journal article › 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
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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638
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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 › Research › peer-review
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352
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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