Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
ORCID: 0000-0002-1402-6899
1 - 5 out of 5Page size: 10
- 2014
- 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 2014Research output: Patent
- 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. US909666Research output: Patent
- 2011
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
- 2010
- Published
Method for identifying region of interest (ROI) in human organ for performing e.g. knee cartilage quantification, involves calculating weight of feature of image in map for minimizing sample size needed to discriminate between groups
Dam, E. B., Nielsen, Mads, Qazi, A. A., Lillholm, Martin & Jørgensen, D. R., 2010, IPC No. G06K-009/00, Patent No. US2010232671-A1, 16 Sep 2010, Priority date 17 Dec 2008, Priority No. US203094PResearch output: Patent
- Published
Two dimensional shape representation manipulation method for improving general procrustes alignment process, involves relating probable relative depth of landmark in three dimensional shape of body part
Chernoff, K., Nielsen, Mads & Lillholm, Martin, 2010, IPC No. G06T-007/00, Patent No. WO2010142595-A1, 16 Dec 2010, Priority date 11 Jun 2009, Priority No. US268370Research output: Patent
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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627
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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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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 › Research › peer-review
Published