Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Cross-disorder comparison of brain structures among 4836 individuals with mental disorders and controls utilizing danish population-based clinical MRI scans
Cerri, S., Nersesjan, V., Klein, K. V., Cóppulo, E. C., Llambias, S. N., Mehdipour Ghazi, M., Nielsen, M. & Benros, M. E., 2026, (E-pub ahead of print) In: Molecular Psychiatry.Research output: Contribution to journal › Journal article › Research › peer-review
Open Access -
General Methods Make Great Domain-Specific Foundation Models: A Case-Study on Fetal Ultrasound
Ambsdorf, J., Munk, A., Llambias, S., Christensen, A. N., Mikolaj, K., Balestriero, R., Tolsgaard, M. G., Feragen, A. & Nielsen, M., 2026, Medical Image Computing and Computer Assisted Intervention, MICCAI 2025 - 28th International Conference, Proceedings, Part VII. Springer, p. 271-281 (Lecture Notes in Computer Science, Vol. 15966 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
File1 Citation (Scopus)2 Downloads (Pure) -
Data Augmentation-Based Unsupervised Domain Adaptation in Medical Imaging
Nørgaard Llambias, S., Nielsen, M. & Mehdipour Ghazi, M., 2025, Image Analysis - 23rd Scandinavian Conference, SCIA 2025, Proceedings. Petersen, J. & Dahl, V. A. (eds.). Springer, Vol. Part 1. p. 177-186 (Lecture Notes in Computer Science, Vol. 15725 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
File13 Downloads (Pure) -
Towards Scalable and Robust White Matter Lesion Localization via Multimodal Deep Learning
Machnio, J., Llambias, S. N., Nielsen, M. & Ghazi, M. M., 2025, arXiv.org, 6 p.Research output: Working paper › Preprint
Open AccessFile7 Downloads (Pure) -
Heterogeneous Learning for Brain Lesion Segmentation, Detection, and Classification
Llambias, S. N., Nielsen, M. & Ghazi, M. M., 2024, Proceedings of the 5th Northern Lights Deep Learning Conference ({NLDL}). PMLR, p. 138-144 (Proceedings of Machine Learning Research, Vol. 233).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Open AccessFile1 Citation (Scopus)276 Downloads (Pure) -
Yucca: A Deep Learning Framework For Medical Image Analysis
Llambias, S. N., Machnio, J., Munk, A., Ambsdorf, J., Nielsen, M. & Ghazi, M. M., 2024, arXiv.org, 8 p.Research output: Working paper › Preprint
File5 Downloads (Pure) -
Active Transfer Learning for 3D Hippocampus Segmentation
Wu, J., Kang, Z., Llambias, S. N., Ghazi, M. M. & Nielsen, M., 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
Open Access