Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
- Published
Identifying recurrent breast cancer patients in national health registries using machine learning
Lauritzen, Andreas, Berg, T., Jensen, M., Lillholm, Martin & Knoop, A., 2023, In: Acta Oncologica. 62, 4, p. 350–357Research output: Contribution to journal › Journal article › Research › peer-review
Image features and the 1-D, 2nd order gaussian derivative jet
Griffin, L. D. & Lillholm, Martin, 2005, Scale Space and PDE Methods in Computer Vision: 5th International Conference, Scale-Space 2005, Hofgeismar, Germany, April 7-9, 2005. Proceedings. Kimmel, R., Sochen, N. A. & Weickert, J. (eds.). Springer, p. 26-37 12 p. (Lecture notes in computer science, Vol. 3459).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Impact of adding breast density to breast cancer risk models: A systematic review
Vilmun, B. M., Vejborg, I., Lynge, E., Lillholm, Martin, Nielsen, Mads, Nielsen, Michael Bachmann & Carlsen, Jonathan Frederik, Jun 2020, In: European Journal of Radiology. 127, 9 p., 109019.Research output: Contribution to journal › Review › Research › peer-review
- Published
Improved Alzheimer's disease diagnostic performance using structural MRI: validation of the MRI combination biomarker that won the CADDementia challenge
Sørensen, L., Lillholm, Martin, Pai, A. S. U., Balas, I., Anker, C., Igel, Christian & Nielsen, Mads, 2015, In: Insights into Imaging. 6, Supplement 1, 1 p., B-0077.Research output: Contribution to journal › Conference abstract in journal › Research
Jet based feature classification
Lillholm, Martin & Steenstrup Pedersen, Kim, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004: ICPR 2004. IEEE, p. 787-790 4 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Larger feature alphabets can improve object recognition even with simpler visual words
Lillholm, Martin & Griffin, L., 2008, In: Perception. 37, Supplement, p. 33-33 1 p.Research output: Contribution to journal › Conference abstract in journal › Research
- Published
Learning density independent texture features
Kallenberg, M. G. J., Nielsen, Mads, Holland, K., Karssemeijer, N., Igel, Christian & Lillholm, Martin, 2016, Breast Imaging: 13th International Workshop, IWDM 2016, Malmö, Sweden, June 19-22, 2016, Proceedings. Tingberg, A., Lång, K. & Timberg, P. (eds.). Springer, p. 299-306 8 p. (Lecture notes in computer science, Vol. 9699).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Linear feature selection in texture analysis - A PLS based method
Marques, J., Igel, Christian, Lillholm, Martin & Dam, E., 2013, In: Machine Vision & Applications. 24, 7, p. 1435-1444 10 p.Research output: Contribution to journal › Journal article › 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
- 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
ID: 152298477
Most downloads
-
1628
downloads
Mammographic texture resemblance generalizes as an independent risk factor for breast cancer
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
628
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 -
339
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