Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
- Published
An Artificial Intelligence–based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload
Lauritzen, Andreas, Rodríguez-Ruiz, A., von Euler-Chelpin, My Catarina, Lynge, Elsebeth, Vejborg, I., Nielsen, Mads, Karssemeijer, N. & Lillholm, Martin, 2022, In: Radiology. 304, 1, p. 41-49Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Assessing Breast Cancer Risk by Combining AI for Lesion Detection and Mammographic Texture
Lauritzen, Andreas, von Euler-Chelpin, My Catarina, Lynge, Elsebeth, Vejborg, I., Nielsen, Mads, Karssemeijer, N. & Lillholm, Martin, 2023, In: Radiology. 308, 2, 8 p., e230227.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Robust cross-vendor mammographic texture models using augmentation-based domain adaptation for long-term breast cancer risk
Lauritzen, Andreas, von Euler-Chelpin, My Catarina, Lynge, Elsebeth, Vejborg, I., Nielsen, Mads, Karssemeijer, N. & Lillholm, Martin, 2023, In: Journal of Medical Imaging. 10, 5, p. 1-16 054003.Research output: Contribution to journal › Journal article › Research › peer-review
- 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
On spatial metamerism in computational vision
Lillholm, Martin, 2004, IT-Universitetet i København. 113 p.Research output: Book/Report › Ph.D. thesis › Research
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
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
A category system on the shape index descriptor of local image structure induced by natural image statistics
Lillholm, Martin & Griffin, L. D., 2006, In: Perception. 35, Supplement, p. 48-49 2 p.Research output: Contribution to journal › Conference abstract in journal › Research
Maximum likelihood metameres for local 2nd order image structure of natural images
Lillholm, Martin & Griffin, L. D., 2007, Scale Space and Variational Methods in Computer Vision: First International Conference, SSVM 2007, Ischia, Italy, May 30 - June 2, 2007. Proceedings. Sgallari, F., Murli, A. & Paragios, N. (eds.). Springer, p. 394-405 12 p. (Lecture notes in computer science, Vol. 4485).Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
- Published
Evaluation of WBAA with registration-based cube propagation for brain atrophy quantification
Lillholm, Martin, Pai, A. S. U., Sørensen, L., Nielsen, Mads, Sporring, Jon, Darkner, Sune & Dam, E., 2013. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
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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626
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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
Published -
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