Research output per year
Research output per year
Personal profile
Primary fields of research
My research is in medical image analysis with focus on imaging biomarkers, primarily of Alzheimer's disease (AD) and chronic obstructive pulmonary disease (COPD). This includes image processing and pattern recognition.
Selected publications (AD imaging biomarkers):
- The Value of Hippocampal Volume, Shape and Texture for 11-year Prediction of Dementia: a Population-Based Study / Achterberg, H.C., Sørensen, L., Wolters, F.J., Niessen, W.J., Vernooij, M.W., Ikram, M.A., Nielsen, M., de Bruijne M. Neurobiology of Aging 81: 58-66, 2019.
- Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry / Sørensen, L., Igel, C., Pai, A., Balas, I., Anker, C., Lillholm, M., Nielsen, M. NeuroImage: Clinical 13: 470-482, 2017.
- Early detection of Alzheimer’s disease using MRI hippocampal texture / Sørensen, L., Igel, C., Hansen, N.L., Osler, M., Lauritzen, M., Rostrup, E., Nielsen, M. Human Brain Mapping 37(3): 1148-1161, 2016.
Selected publications (AD progression modeling using imaging biomarkres)
- Robust parametric modeling of Alzheimer's disease progression / Ghazi, M.M., Nielsen, M., Pai, A., Cardoso, M.J., Modat, M., Ourselin, S., and Sørensen, L. arXiv:1908.05338, 2019.
- Training recurrent neural networks robust to incomplete data: application to Alzheimer's disease progression modeling / Ghazi, M.M., Nielsen, M., Pai, A., Cardoso, M.J., Modat, M., Ourselin, S., and Sørensen, L. Medical Image Analysis 53: 39-46, 2019.
Selected publications (COPD imaging biomarkers):
- Transfer Learning for Multi-Center Classification of Chronic Obstructive Pulmonary Disease / Cheplygina, V., Peña, I.P., Pedersen, J.J.H, Lynch, D.A., Sørensen, L., de Bruijne, M. IEEE Journal of Biomedical and Health Informatics, 2018.
- Texture-Based Analysis of COPD: a Data-Driven Approach / Sørensen, L., Nielsen, M., Lo, P., Ashraf, H., Pedersen, J.J.H., de Bruijne, M. L. Sørensen, M. Nielsen, P. Lo, H. Ashraf, J.J.H. Pedersen, and M. de Bruijne. IEEE Transactions on Medical Imaging 31(1): 70-78, 2012.
- Quantitative analysis of pulmonary emphysema using local binary patterns / Sørensen, L., Shaker S.B., de Bruijne, M. IEEE Transactions on Medical Imaging 29(2): 559-569, 2010.
Selected publications (other)
- (MRI hippocampal texture in depression)
Subclinical depressive symptoms during late midlife and structural brain alterations: A longitudinal study of Danish men born in 1953 / Osler, M., Sørensen, L., Rozing, M., Calvo, O., Nielsen, M., Rostrup, E. Human Brain Mapping 39(4): 1789-1795, 2018. - (1st place in CADDementia challenge)
Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on
structural MRI: the CADDementia challenge / Bron, E.E., ..., Sørensen, L., et al. NeuroImage 111: 562-579, 2015. - (Dissimilarity-based multiple instance learning)
Dissimilarity-based multiple instance learning / Sørensen, L., Loog, M., Tax, D.M.J., Lee, W.-J., de Bruijne, M., Duin, R.P.W. In: Statistical, Structural and Syntactic Pattern Recognition (S+SSPR), 2010.
Resources:
Current research
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Hippocampal texture as an early T1-weighted structural MRI biomarker of Alzheimer's disease
- Combination of MRI biomarkers for imporved Alzheimer's disease diagnosis
- Alzheimer's disease progression modelling using multiple biomarkers
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Keywords
- Faculty of Science
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Research output
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Knowledge Distillation for Semi-supervised Domain Adaptation
Orbes-Arteaga, M., Cardoso, J., Sørensen, L., Igel, C., Ourselin, S., Modat, M., Nielsen, M. & Pai, A., 1 Jan 2019, OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging - 2nd International Workshop, OR 2.0 2019, and 2nd International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Proceedings. Zhou, L., Sarikaya, D., Kia, S. M., Speidel, S., Malpani, A., Hashimoto, D., Habes, M., Löfstedt, T., Ritter, K. & Wang, H. (eds.). Springer VS, p. 68-76 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11796 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Multi-domain adaptation in brain MRI through paired consistency and adversarial learning
Orbes-Arteaga, M., Varsavsky, T., Sudre, C. H., Eaton-Rosen, Z., Haddow, L. J., Sørensen, L., Nielsen, M., Pai, A., Ourselin, S., Modat, M., Nachev, P. & Cardoso, M. J., 2019, Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data First MICCAI Workshop, DART 2019 and First International Workshop, MIL3ID 2019 Shenzhen, Held in Conjunction with MICCAI 2019 Shenzhen, 2019 Proceedings. Wang, Q., Milletari, F., Rieke, N., Nguyen, H. V., Roysam, B., Albarqouni, S., Cardoso, M. J., Xu, Z., Kamnitsas, K., Patel, V., Jiang, S., Zhou, K., Luu, K. & Le, N. (eds.). Springer VS, p. 54-62 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11795 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
Orbes-Arteaga, M., Sørensen, L., Cardoso, J., Modat, M., Ourselin, S., Sommer, S. H., Nielsen, M., Igel, C. & Pai, A. S. U., 2019, Proceedings, SPIE 10949, Medical Imaging 2019: Image Processing . SPIE - International Society for Optical Engineering, 6 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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The value of hippocampal volume, shape, and texture for 11-year prediction of dementia: a population-based study
Achterberg, H. C., Sørensen, L., Wolters, F. J., Niessen, W. J., Vernooij, M. W., Ikram, M. A., Nielsen, M. & de Bruijne, M., 2019, In: Neurobiology of Aging. 81, p. 58-66Research output: Contribution to journal › Journal article › Research › peer-review
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Training recurrent neural networks robust to incomplete data: application to Alzheimer’s disease progression modeling
Mehdipour Ghazi, M., Nielsen, M., Pai, A. S. U., Cardoso, M. J., Modat, M., Ourselin, S. & Sørensen, L., Apr 2019, In: Medical Image Analysis. 53, p. 39-46Research output: Contribution to journal › Journal article › Research › peer-review
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UNSUPERVISED MACHINE LEARNING ON BASELINE BRAIN MRI IDENTIFIES MCI SUBGROUP WITH A FASTER DECLINE OVER TWO YEARS COMPARED TO CLASSICAL HIPPOCAMPAL SPARING AD SUBTYPE
Sørensen, L., Pai, A., Nielsen, M., Leverenz, J. B. & Pillai, J. A., 2019, In: Alzheimer's & Dementia. 15, 7, p. P1420 1 p., P4-326.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
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Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination
Sørensen, L. & Nielsen, M., 15 May 2018, In: Journal of Neuroscience Methods. 302, SI, p. 66-74Research output: Contribution to journal › Journal article › Research › peer-review
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HIPPOCAMPAL TEXTURE IN HEALTHY COGNITION AND MILD COGNITIVE IMPAIRMENT: THE IMPACT OF AMYLOID BURDEN AND SEX
Caldwell, J. Z. K., Pai, A., Sørensen, L., Kaylegian, J., Cummings, J. L. & Banks, S. J., 2018, In: Alzheimer's & Dementia. 14, 7, p. P874-P875 P2-426.Research output: Contribution to journal › Conference abstract in journal › Research
Datasets
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Computed Tomography Emphysema Database
xfj310, X. (Creator), Shaker, S. B. (Creator) & de Bruijne, M. (Creator), DIKU, Univ. of Copenhagen, 2013
http://image.diku.dk/emphysema_database/
Dataset