Martin Lillholm
Martin Lillholm
Associate Prof. Univiersity of Copenhagen, Senior Researcher, Biomediq
Verified email at
Cited by
Cited by
Quaternions, interpolation and animation
EB Dam, M Koch, M Lillholm
Datalogisk Institut, Københavns Universitet, 1998
Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring
M Kallenberg, K Petersen, M Nielsen, AY Ng, P Diao, C Igel, CM Vachon, ...
IEEE transactions on medical imaging 35 (5), 1322-1331, 2016
Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry
L Sørensen, C Igel, A Pai, I Balas, C Anker, M Lillholm, M Nielsen, ...
NeuroImage: Clinical 13, 470-482, 2017
Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative
EB Dam, M Lillholm, J Marques, M Nielsen
Journal of Medical imaging 2 (2), 024001, 2015
Feature-based image analysis
M Lillholm, M Nielsen, LD Griffin
International Journal of Computer Vision 52 (2), 73-95, 2003
Breast tissue segmentation and mammographic risk scoring using deep learning
K Petersen, M Nielsen, P Diao, N Karssemeijer, M Lillholm
International workshop on digital mammography, 88-94, 2014
What do features tell about images?
M Nielsen, M Lillholm
International Conference on Scale-Space Theories in Computer Vision, 39-50, 2001
Eye movements in gaze interaction
E Møllenbach, JP Hansen, M Lillholm
Journal of Eye Movement Research 6 (2), 2013
Basic image features (bifs) arising from approximate symmetry type
LD Griffin, M Lillholm, M Crosier, J Van Sande
International Conference on Scale Space and Variational Methods in Computer …, 2009
Single gaze gestures
E Møllenbach, M Lillholm, A Gail, JP Hansen
Proceedings of the 2010 symposium on eye-tracking research & applications …, 2010
Optimised region of interest selection
EB Dam, M Nielsen, A Qazi, M Lillholm, DR Jørgenson
US Patent 8,538,102, 2013
Single stroke gaze gestures
E Møllenbach, JP Hansen, M Lillholm, AG Gale
CHI'09 Extended Abstracts on Human Factors in Computing Systems, 4555-4560, 2009
Mammographic texture resemblance generalizes as an independent risk factor for breast cancer
M Nielsen, CM Vachon, CG Scott, K Chernoff, G Karemore, ...
Breast Cancer Research 16 (2), 1-8, 2014
Natural image profiles are most likely to be step edges
LD Griffin, M Lillholm, M Nielsen
Vision research 44 (4), 407-421, 2004
Symmetry sensitivities of derivative-of-gaussian filters
LD Griffin, M Lillholm
IEEE transactions on pattern analysis and machine intelligence 32 (6), 1072-1083, 2009
On image reconstruction from multiscale top points
F Kanters, M Lillholm, R Duits, B Janssen, B Platel, L Florack, ...
International Conference on Scale-Space Theories in Computer Vision, 431-442, 2005
Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
RR Winkel, M von Euler-Chelpin, M Nielsen, K Petersen, M Lillholm, ...
BMC cancer 16 (1), 1-12, 2016
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
E Jimenez-Solem, TS Petersen, C Hansen, C Hansen, C Lioma, C Igel, ...
Scientific reports 11 (1), 1-12, 2021
Sensitivity of screening mammography by density and texture: a cohort study from a population-based screening program in Denmark
M von Euler-Chelpin, M Lillholm, I Vejborg, M Nielsen, E Lynge
Breast Cancer Research 21 (1), 1-7, 2019
The combined effect of mammographic texture and density on breast cancer risk: a cohort study
JOP Wanders, CH van Gils, N Karssemeijer, K Holland, M Kallenberg, ...
Breast Cancer Research 20 (1), 1-10, 2018
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