Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
ORCID: 0000-0002-1402-6899
1 - 5 ud af 5Pr. side: 10
- 2014
- Udgivet
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, Prioritetsdato 4 dec. 2014Publikation: Patent
- Udgivet
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 nr. A61B-005/00, Patentnr. US2014357978-A1, 4 dec. 2014, Prioritetsdato 4 jun. 2013, Prioritetsnr. US909666Publikation: 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 nr. G06T-007/00, Patentnr. WO2011151242-A1, 8 dec. 2011, Prioritetsdato 1 jun. 2010, Prioritetsnr. GB009101Publikation: Patent
- 2010
- Udgivet
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 nr. G06K-009/00, Patentnr. US2010232671-A1, 16 sep. 2010, Prioritetsdato 17 dec. 2008, Prioritetsnr. US203094PPublikation: Patent
- Udgivet
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 nr. G06T-007/00, Patentnr. WO2010142595-A1, 16 dec. 2010, Prioritetsdato 11 jun. 2009, Prioritetsnr. US268370Publikation: Patent
ID: 152298477
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Mammographic texture resemblance generalizes as an independent risk factor for breast cancer
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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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Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative
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