Mads Nielsen
Professor
Pioneer AI (P1AI)
Øster Voldgade 3
1350 København K
- 2024
- Published
AI supported fetal echocardiography with quality assessment
Taksoee-Vester, C. A., Mikolaj, K., Bashir, Z., Christensen, A. N., Petersen, Olav Bennike Bjørn, Sundberg, K., Feragen, A., Svendsen, Morten B.S., Nielsen, Mads & xgz472, xgz472, 2024, In: Scientific Reports. 14, 1, 9 p., 5809.Research output: Contribution to journal › Journal article › peer-review
- Published
CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning From Sporadic Temporal Data
Mehdipour Ghazi, Mostafa, Sørensen, L., Ourselin, S. & Nielsen, Mads, 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 1, p. 792-802Research output: Contribution to journal › Journal article › peer-review
- Published
Comparative analysis of multimodal biomarkers for amyloid-beta positivity detection in Alzheimer's disease cohorts
Mehdipour Ghazi, Mostafa, Selnes, P., Timón-Reina, S., Tecelão, S., Ingala, S., Bjørnerud, A., Kirsebom, B. E., Fladby, T. & Nielsen, Mads, 2024, In: Frontiers in Aging Neuroscience. 16, 1345417.Research output: Contribution to journal › Journal article › peer-review
- E-pub ahead of print
Population-wide evaluation of artificial intelligence and radiologist assessment of screening mammograms
Kühl, J., Elhakim, M. T., Stougaard, S. W., Rasmussen, B. S. B., Nielsen, Mads, Gerke, O., Larsen, L. B. & Graumann, O., 2024, (E-pub ahead of print) In: European Radiology. 12 p.Research output: Contribution to journal › Journal article › peer-review
- 2023
- Published
Active Transfer Learning for 3D Hippocampus Segmentation
Wu, J., Kang, Zhongfeng, Llambias, Sebastian Nørgaard, Mehdipour Ghazi, Mostafa & Nielsen, Mads, 2023, Medical Image Learning with Limited and Noisy Data - 2nd International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Proceedings. Xue, Z., Antani, S., Zamzmi, G., Yang, F., Rajaraman, S., Liang, Z., Huang, S. X. & Linguraru, M. G. (eds.). Springer, p. 224-234 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14307 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
An Analysis of Spatial-Spectral Dependence in Hyperspectral Autoencoders
Laprade, W. M., Westergaard, Jesper Cairo, Nielsen, J., Nielsen, Mads & Dahl, A. B., 2023, Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings. Gade, R., Felsberg, M. & Kämäräinen, J-K. (eds.). Springer, p. 191-202 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13886 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › 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 › peer-review
- Published
Breast density and risk of breast cancer
Lynge, Elsebeth, Vejborg, I., Lillholm, Martin, Nielsen, Mads, Napolitano, George & von Euler-Chelpin, My Catarina, 2023, In: International Journal of Cancer. 152, 6, p. 1150-1158 9 p.Research output: Contribution to journal › Journal article › peer-review
- Published
Deep Learning-Based Assessment of Cerebral Microbleeds in COVID-19
Ferrer, N. R., Vendela Sagar, M., Klein, Kiril Vadimovic, Kruuse, Christina Rostrup, Nielsen, Mads & Mehdipour Ghazi, Mostafa, 2023, 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. IEEE Computer Society Press, p. 1-4 4 p. (Proceedings - International Symposium on Biomedical Imaging, Vol. 2023-April).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Diagnostic test accuracy study of a commercially available deep learning algorithm for ischemic lesion detection on brain MRIs in suspected stroke patients from a non-comprehensive stroke center
Krag, C. H., Müller, F. C., Gandrup, K. L., Raaschou, H., Andersen, Michael Brun, Brejnebøl, M. W., Sagar, M. V., Bojsen, J. A., Rasmussen, B. S., Graumann, O., Nielsen, Mads, Kruuse, Christina Rostrup & Boesen, Mikael Ploug, 2023, In: European Journal of Radiology. 168, 8 p., 111126.Research output: Contribution to journal › Journal article › peer-review
- Published
Instance-Specific Augmentation of Brain MRIs with Variational Autoencoders
Middleton, Jon Anthony, Bauer, Marko, Johansen, Jacob, Nielsen, Mads, Sommer, Stefan Horst & Pai, A. S. U., 2023, Medical Applications with Disentanglements : First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Springer, p. 49-58 (Lecture Notes in Computer Science, Vol. 13823).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Partial feedback online transfer learning with multi-source domains
Kang, Zhongfeng, Nielsen, Mads, Yang, B. & Mehdipour Ghazi, Mostafa, 2023, In: Information Fusion. 89, p. 29-40Research output: Contribution to journal › Journal article › 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 › peer-review
- 2022
- Published
Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts
Kutuzova, S., Krause, Oswin, McCloskey, D., Nielsen, Mads & Igel, Christian, Jan 2022, arXiv.org, 29 p.Research output: Working paper › Preprint › Research
- Published
A buffered online transfer learning algorithm with multi-layer network
Kang, Zhongfeng, Yang, B., Nielsen, Mads, Deng, L. & Yang, S., 2022, In: Neurocomputing. 488, p. 581-597 17 p.Research output: Contribution to journal › Journal article › peer-review
- 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 › peer-review
- Published
Augmentation based unsupervised domain adaptation
Orbes-Arteaga, M., Varsavsky, T., Sørensen, L., Nielsen, Mads, Pai, A. S. U., Ourselin, S., Modat , M. & Cardoso, M. J., 2022, arXiv.org, 12 p.Research output: Working paper › Preprint › Research
- Published
- Published
Information Bottleneck: Exact Analysis of (Quantized) Neural Networks
Lorenzen, S. S., Igel, Christian & Nielsen, Mads, 2022, arXiv.org, 19 p.Research output: Working paper › Preprint › Research
- Published
Machine learning and deep learning applications in microbiome research
Hernandez Medina, Ricardo, Kutuzova, Svetlana, Nielsen, Knud Nor, Johansen, Joachim, Hansen, Lars Hestbjerg, Nielsen, Mads & Rasmussen, Simon, 2022, In: ISME Communications. 2, 7 p., 98.Research output: Contribution to journal › Journal article › peer-review
- 2021
- Published
Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark
Lorenzen, S. S., Nielsen, Mads, Jimenez-Solem, E., Petersen, Tonny Studsgaard, Perner, Anders, Thorsen-Meyer, H., Igel, Christian & Sillesen, Martin Hylleholt, 23 Sep 2021, In: Scientific Reports. 11, 1, 10 p., 18959.Research output: Contribution to journal › Journal article › peer-review
- Published
Bi-modal Variational Autoencoders for Metabolite Identification Using Tandem Mass Spectrometry
Kutuzova, S., Igel, Christian, Nielsen, Mads & McCloskey, D., 2021, bioRxiv, 22 p.Research output: Working paper › Preprint › Research
- Published
CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data
Mehdipour Ghazi, Mostafa, Sørensen, L., Ourselin, S. & Nielsen, Mads, 2021, arXiv.org, 11 p.Research output: Working paper › Preprint › Research
- Published
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Jimenez-Solem, E., Petersen, T. S., Hansen, C., Hansen, C., Lioma, C., Igel, C., Boomsma, W., Krause, O., Lorenzen, S., Selvan, R., Petersen, J., Nyeland, M. E., Ankarfeldt, M. Z., Virenfeldt, G. M., Winther-Jensen, M., Linneberg, A., Ghazi, M. M., Detlefsen, N., Lauritzen, A. D., Smith, A. G. & 15 others, , 2021, In: Scientific Reports. 11, 1, 12 p., 3246.Research output: Contribution to journal › Journal article › peer-review
- Published
Extension of Plant Phenotypes by the Foliar Microbiome
Hawkes, C. V., Kjøller, Rasmus, Raaijmakers, J. M., Riber, Leise, Christensen, Svend, Rasmussen, Simon, Christensen, Jan H., Dahl, A. B., Westergaard, Jesper Cairo, Nielsen, Mads, Brown-Guedira, G. & Hansen, Lars Hestbjerg, 2021, In: Annual Review of Plant Biology. 72, p. 823-846 24 p.Research output: Contribution to journal › Journal article › peer-review
- Published
Information Processing in Medical Imaging: 27th International Conference, IPMI 2021, Virtual Event, June 28–June 30, 2021, Proceedings
Feragen, A. (ed.), Sommer, Stefan Horst (ed.), Schnabel, J. (ed.) & Nielsen, Mads (ed.), 2021, Springer. 782 p. (Lecture Notes in Computer Science, Vol. 12729).Research output: Book/Report › Anthology › peer-review
Lesion-wise evaluation for effective performance monitoring of small object segmentation
Groothuis, I., Sudre, C. H., Ingala, S., Barnes, J., Gispert, J. D., Sørensen, L., Pai, A., Nielsen, Mads, Ourselin, S., Cardoso, M. J., Barkhof, F. & Modat, M., 2021, Medical Imaging 2021: Image Processing. Isgum, I. & Landman, B. A. (eds.). SPIE, p. 1-8 1159608. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 11596).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Robust parametric modeling of Alzheimer's disease progression
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A., Modat, M., Jorge Cardoso, M., Ourselin, S. & Sørensen, L., 2021, In: NeuroImage. 225, 12 p., 117460.Research output: Contribution to journal › Journal article › peer-review
- 2020
- 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 › peer-review
- Published
Lung Segmentation from Chest X-rays using Variational Data Imputation
Selvan, Raghav, Dam, Erik Bjørnager, Rischel, S., Sheng, K., Nielsen, Mads & Pai, A., 20 May 2020, In: OpenReview.net. 7 p.Research output: Contribution to journal › Conference article
- Published
Chronic Obstructive Pulmonary Disease Quantification Using CT Texture Analysis and Densitometry: Results From the Danish Lung Cancer Screening Trial
Sørensen, L., Nielsen, Mads, Petersen, Jens, Pedersen, J. H., Dirksen, A. & de Bruijne, Marleen, 2020, In: American Journal of Roentgenology. 214, 6, p. 1269-1279Research output: Contribution to journal › Journal article › peer-review
- Published
Inflammatory pathway analytes predicting rapid cognitive decline in MCI stage of Alzheimer’s disease
Pillai, J. A., Bena, J., Bebek, G., Bekris, L. M., Bonner-Jackson, A., Kou, L., Pai, A., Sørensen, L., Nielsen, Mads, Rao, S. M., Chance, M., Lamb, B. T. & Leverenz, J. B., 2020, In: Annals of Clinical and Translational Neurology. 7, 7, p. 1225-1239 15 p.Research output: Contribution to journal › Journal article › peer-review
- Published
Kunstig intelligens til cancerdiagnostik i brystkræftscreening
Elhakim, M. T., Graumann, O., Brønsro Larsen, L., Nielsen, Mads & Rasmussen, B. S., 2020, In: Ugeskrift for Laeger. 182, 16, p. 1488-1492 V06200423.Research output: Contribution to journal › Journal article › peer-review
- Published
Position paper on COVID-19 imaging and AI: From the clinical needs and technological challenges to initial AI solutions at the lab and national level towards a new era for AI in healthcare
Greenspan, H., Estepar, R. S. J., Niessen, W. J., Siegel, E. & Nielsen, Mads, 2020, In: Medical Image Analysis. 66, 11 p., 101800.Research output: Contribution to journal › Journal article › peer-review
- 2019
- Published
Increasing Accuracy of Optimal Surfaces Using Min-marginal Energies
Petersen, Jens, Arias-Lorza, A. M., Selvan, Raghav, Bos, D., van der Lugt, A., Pedersen, J. H., Nielsen, Mads & de Bruijne, Marleen, 1 Jan 2019, In: IEEE Transactions on Medical Imaging. 38, 7, p. 1559-1568 8599009.Research output: Contribution to journal › Journal article › peer-review
- Published
Knowledge Distillation for Semi-supervised Domain Adaptation
Orbes-Arteaga, M., Cardoso, J., Sørensen, L., Igel, Christian, Ourselin, S., Modat, M., Nielsen, Mads & 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
- Published
Change in mammographic density across birth cohorts of Dutch breast cancer screening participants
Napolitano, George, Lynge, Elsebeth, Lillholm, Martin, Vejborg, I. M. M., van Gils, C. H., Nielsen, Mads & Karssemeijer, N., 2019, In: International Journal of Cancer. 145, 11, p. 2954-2962 9 p.Research output: Contribution to journal › Journal article › peer-review
- Published
MRI Biomarkers Improve Disease Progression Modeling-Based Prediction of Cognitive Decline
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Modat , M., Cardoso , J., Ourselin, S. & Sorensen, L., 2019. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research
- Published
Measurement challenge: protocol for international case–control comparison of mammographic measures that predict breast cancer risk
Dench, E., Bond-smith, D., Darcey, E., Lee, G., Aung, Y. K., Chan, A., Cuzick, J., Ding, Z. Y., Evans, C. F., Harvey, J., Highnam, R., Hsieh, M., Kontos, D., Li, S., Mariapun, S., Nickson, C., Nguyen, T. L., Pertuz, S., Procopio, P., Rajaram, N. & 12 others, , 2019, In: BMJ Open. 9, 12, p. 1-6 e031041.Research output: Contribution to journal › Journal article › peer-review
- Published
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, Mads, 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
- Published
On the initialization of long short-term memory networks
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A., Modat, M., Cardoso, M. J., Ourselin, S. & Sørensen, L., 2019, Neural Information Processing - 26th International Conference, ICONIP 2019, Proceedings. Gedeon, T., Wong, K. W. & Lee, M. (eds.). Springer VS, p. 275-286 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11953 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
Orbes-Arteaga, M., Sørensen, L., Cardoso , J., Modat , M., Ourselin, S., Sommer, Stefan Horst, Nielsen, Mads, Igel, Christian & 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
- Published
Sensitivity of screening mammography by density and texture: a cohort study from a population-based screening program in Denmark
von Euler-Chelpin, My Catarina, Lillholm, Martin, Vejborg, I., Nielsen, Mads & Lynge, Elsebeth, 2019, In: Breast Cancer Research. 21, 1Research output: Contribution to journal › Journal article › peer-review
- Published
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, Mads & de Bruijne, Marleen, 2019, In: Neurobiology of Aging. 81, p. 58-66Research output: Contribution to journal › Journal article › peer-review
- Published
Training recurrent neural networks robust to incomplete data: application to Alzheimer’s disease progression modeling
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Cardoso, M. J., Modat, M., Ourselin, S. & Sørensen, L., 2019, In: Medical Image Analysis. 53, p. 39-46Research output: Contribution to journal › Journal article › peer-review
- Published
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, Mads, 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 › peer-review
- 2018
- Published
Subclinical depressive symptoms during late midlife and structural brain alterations: A longitudinal study of Danish men born in 1953
Osler, Merete, Sørensen, L., Rozing, M., Calvo, O. P., Nielsen, Mads & Rostrup, E., Apr 2018, In: Human Brain Mapping. 39, 4, p. 1789-1795Research output: Contribution to journal › Journal article › peer-review
- Published
Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination
Sørensen, L. & Nielsen, Mads, 2018, In: Journal of Neuroscience Methods. 302, SI, p. 66-74Research output: Contribution to journal › Journal article › peer-review
- Published
Robust training of recurrent neural networks to handle missing data for disease progression modeling
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Cardoso, M. J., Modat, M., Ourselin, S. & Sørensen, L., 2018. 9 p.Research output: Contribution to conference › Paper › Research
- Published
Screening mammography: benefit of double reading by breast density
von Euler-Chelpin, My Catarina, Lillholm, Martin, Napolitano, George, Vejborg, I., Nielsen, Mads & Lynge, Elsebeth, 2018, In: Breast Cancer Research and Treatment. 171, 3, p. 767-776 10 p.Research output: Contribution to journal › Journal article › peer-review
ID: 542361
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Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI
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Smoothing images creates corners
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Distribution, size, shape, growth potential and extent of abdominal aortic calcified deposits predict mortality in postmenopausal women
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