Martin Lillholm

Professor

ORCID: 0000-0002-1402-6899

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A unifying framework for automatic and semi-automatic segmentation of vertebrae from radiographs using sample-driven active shape models
Mysling, P., Petersen, P. K., Nielsen, Mads & Lillholm, Martin, 2013, In: Machine Vision & Applications. 24, 7, p. 1421–1434 14 p.
Research output: Contribution to journal › Journal article › Research › peer-review
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

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ID: 152298477

1630 downloads
Mammographic texture resemblance generalizes as an independent risk factor for breast cancer
Research output: Contribution to journal › Journal article › Research › peer-review
Published
631 downloads
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
Published
341 downloads
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

Research