Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
- 2013
- Published
Localized cerebral atrophy acceleration during Alzheimer’s disease
Pai, A. S. U., Sørensen, L., Darkner, Sune, Lillholm, Martin, Dam, E. B., Sporring, Jon & Nielsen, Mads, 2013, In: Alzheimer's & Dementia. 9, 4, Supplement, p. P36–P37 2 p., IC-P-059.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
- Published
Localized cerebral atrophy acceleration during Alzheimer’s disease
Pai, A. S. U., Sørensen, L., Darkner, Sune, Lillholm, Martin, Dam, E. B., Sporring, Jon & Nielsen, Mads, 2013, In: Alzheimer's & Dementia. 9, 4, Supplement, p. P151 1 p., O1-10-06.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
- 2012
- Published
Shape-based assessment of vertebral fracture risk in postmenopausal women using discriminative shape alignment
Crimi, A., Loog, M., de Bruijne, Marleen, Nielsen, Mads & Lillholm, Martin, 2012, In: Academic Radiology. 19, 4, p. 446-454 9 p.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Fully automatic cartilage morphometry for knee MRI from the OAI
Dam, E., Marques, J., Zaim, S., Fuerst, T., Genant, H., Lillholm, Martin & Nielsen, Mads, 2012. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
- Published
Automatic analysis of trabecular bone structure from knee MRI
Marques, J., Granlund, R., Lillholm, Martin, Pettersen, P. C. & Dam, E. B., 2012, In: Computers in Biology and Medicine. 42, 7, p. 735-742 8 p.Research output: Contribution to journal › Journal article › 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
Evaluation of a novel approach for automatic delineation of vertebral contours in radiographs
Mysling, P., Petersen, P. K., Nielsen, Mads & Lillholm, Martin, 2012, In: Osteoporosis International. 23, Supplement 2, p. S250-S250 1 p., P439.Research output: Contribution to journal › Conference abstract in journal › Research
- Published
Automatic quantification of tibio-femoral contact area and congruity
Tummala, S., Nielsen, Mads, Lillholm, Martin, Christiansen, C. & Dam, Erik Bjørnager, 2012, In: I E E E Transactions on Medical Imaging. 31, 7, p. 1404-1412 9 p.Research output: Contribution to journal › Journal article › Research › peer-review
- 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
ID: 152298477
Most downloads
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1632
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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
Published -
635
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 -
348
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