xfj310 xfj310
Lektor
Machine Learning
Universitetsparken 1, 2100 København Ø
- Udgivet
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. & xfj310, xfj310, 2019, I : Medical Image Analysis. 53, s. 39-46Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Combining the boundary shift integral and tensor-based morphometry for brain atrophy estimation
Michalkiewicz, M. D., Pai, A. S. U., Leung, K. K., Sommer, Stefan Horst, Darkner, Sune, xfj310, xfj310, Sporring, Jon & Nielsen, Mads, 2016, Medical imaging 2016: Image processing. Styner, M. A. & Angelini, E. D. (red.). SPIE - International Society for Optical Engineering, 6 s. 978406. (Progress in Biomedical Optics and Imaging).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Hippocampal texture predicts ad conversion in amyloid positive mild cognitively impaired subjects
Nielsen, Mads, Igel, Christian & xfj310, xfj310, 2015, I : Neurodegenerative Diseases. 15, Suppl. 1, s. 262 1 s., ADPD5-0947.Publikation: Bidrag til tidsskrift › Konferenceabstrakt i tidsskrift › Forskning
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Hippocampus MRI T1 texture's relation to established Alzheimer's disease biomarkers and prediction of progression
Nielsen, Mads, xfj310, xfj310, Pai, A. S. U., Igel, Christian & Lillholm, Martin, 2015. 1 s.Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › fagfællebedømt
- Udgivet
Method for computerized classification of e.g. computed tomography image, of lung of patient suffering from e.g. non-focal lung disease, involves combining probabilities within regions of interest to obtain quantitative fused probability
Nielsen, Mads, de Bruijne, Marleen & xfj310, xfj310, 2011, IPC nr. G06K-009/00, Patentnr. US2011280457-A1, 17 nov. 2011, Prioritetsdato 11 maj 2010, Prioritetsnr. US333513PPublikation: Patent
- Udgivet
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
Orbes-Arteaga, M., xfj310, xfj310, 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 s.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 MRIs
Orbes-Arteaga, M., Cardoso, M. J., xfj310, xfj310, Modat, M., Ourselin, S., Nielsen, Mads & Pai, A. S. U., 2018. 8 s.Publikation: Konferencebidrag › Paper › Forskning
- Udgivet
Knowledge Distillation for Semi-supervised Domain Adaptation
Orbes-Arteaga, M., Cardoso, J., xfj310, xfj310, 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. (red.). Springer VS, s. 68-76 9 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11796 LNCS).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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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., xfj310, xfj310, 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. (red.). Springer VS, s. 54-62 9 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11795 LNCS).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Subclinical depressive symptoms during late midlife and structural brain alterations: A longitudinal study of Danish men born in 1953
Osler, Merete, xfj310, xfj310, Rozing, M., Calvo, O. P., Nielsen, Mads & Rostrup, E., apr. 2018, I : Human Brain Mapping. 39, 4, s. 1789-1795Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI
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Pattern Recognition-Based Analysis of COPD in CT
Publikation: Bog/antologi/afhandling/rapport › Ph.d.-afhandling
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Differential diagnosis of mild cognitive impairment and Alzheimer’s disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry
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