L.F. Volmer
Recent publications
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Koutsouvelis, P., Ermans, S. J. E., Volmer, L., Hoeberigs, C. M., Brecheisen, R., Eekers, D. B. P., Schijns, O. E. M. G., & Dekker, A. (2026). Localizing the epileptogenic zone using deep learning and neuroimaging: A systematic review. SEIZURE-EUROPEAN JOURNAL OF EPILEPSY, 137, 121-137. https://doi.org/10.1016/j.seizure.2026.03.002More information about this publication
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Zhou, C., Zhang, X., van Dijk, D. P. J., Rensen, S. S., Zhang, J., Volmer, L., Wee, L., & Olde Damink, S. W. M. (2026). Independent validation of the Mosamatic deep learning automated skeletal muscle and adipose tissue segmentation tool in an external Chinese cancer patient cohort. BJR Artificial Intelligence, 3(1), 021. https://doi.org/10.1093/bjrai/ubaf021More information about this publication
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Koutsouvelis, P., Gazda, M., Volmer, L., Amirrajab, S., Barbierik, K., Setlak, B., Gazda, J., & Drotar, P. (2026). Large-Scale Modality-Invariant Foundation Models for Brain Mri Analysis: Application to Lesion Segmentation. In ISBI 2026 - 23rd IEEE International Symposium on Biomedical Imaging (Vol. 2026-April). IEEE Computer Society. https://doi.org/10.1109/ISBI61048.2026.11515369More information about this publication
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Van Der Velden, A. L., Knapen, R. R. M. M., Rahmani, H., Volmer, L., Simon, S. R., Verhagen, C. A. M., Burgmans, M. C., Dekker, A. L. A. J., Wildberger, J. E., Van Dam, R. M., Brecheisen, R., & Van Der Leij, C. (2025). The influence of AI on surgical and ablative treatments for colorectal liver metastases: a review of the current literature. Insights into Imaging, 16(1), Article 253. https://doi.org/10.1186/s13244-025-02072-9More information about this publication
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van der Velden, A. L., Verhagen, C. A. M., Gholamiankhah, F., Rahmani, H., van Dam, R. M., van Duijn-de Vreugd, J. J., Simon, S. R., Hendriks, P., van Erp, G. C. M., Knapen, R. R. M. M., Volmer, L., Overduin, K., Braak, J. P. B. M., Bale, R., Laimer, G., Lanocita, R., Meijerink, M. R., Kampfer, Y., Denys, A., ... van der Leij, C. (2025). Prospective Registry Study on Thermal Liver Ablation of Primary and Secondary Liver Tumours Named the A-IMAGIO Study. Cardiovascular and Interventional Radiology, 48(8), 1193-1199. https://doi.org/10.1007/s00270-025-04093-9More information about this publication
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Liu, Z., Li, W., Cui, Y., Chen, X., Pan, X., Ye, G., Wu, G., Liao, Y., Volmer, L., Wee, L., Dekker, A., Han, C., Liu, Z., & Shi, Z. (2025). Label-efficient transformer-based framework with self-supervised strategies for heterogeneous lung tumor segmentation. Expert Systems with Applications, 269, Article 126364. https://doi.org/10.1016/j.eswa.2024.126364More information about this publication
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Aberle, M. R., Coolsen, M. M. E., Wenmaekers, G., Volmer, L., Brecheisen, R., van Dijk, D., Wee, L., Van Dam, R. M., de Vos-Geelen, J., Rensen, S. S., & Damink, S. W. M. O. (2025). Skeletal muscle is independently associated with grade 3-4 toxicity in advanced stage pancreatic ductal adenocarcinoma patients receiving chemotherapy. Clinical Nutrition ESPEN, 65, 134-143. https://doi.org/10.1016/j.clnesp.2024.11.004More information about this publication
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Choudhury, A., Volmer, L., Martin, F., Fijten, R., Wee, L., Dekker, A., & van Soest, J. (2025). Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study. JMIR AI, 4, Article e60847. https://doi.org/10.2196/60847More information about this publication
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van Dijk, D. P. J., Volmer, L. F., Brecheisen, R., Martens, B., Dolan, R. D., Bryce, A. S., Chang, D. K., McMillan, D. C., Stoot, J. H. M. B., West, M. A., Rensen, S. S., Dekker, A., Wee, L., Damink, S. W. M. O., & Body Composition Collaborative (2024). External validation of a deep learning model for automatic segmentation of skeletal muscle and adipose tissue on abdominal CT images. British Journal of Radiology, 97(1164), 2015-2023. https://doi.org/10.1093/bjr/tqae191More information about this publication
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Mateus, P., Volmer, L., Wee, L., Aerts, H. J. W. L., Hoebers, F., Dekker, A., & Bermejo, I. (2023). Image based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimization. Scientific Reports, 13(1), Article 18176. https://doi.org/10.1038/s41598-023-45486-5More information about this publication