Kleesiek, Jens

Deep MRI brain extraction: A 3D convolutional neural network for skull stripping

Kleesiek, J., Urban, G., Hubert, A., Schwarz, D., Maier-Hein, K., Bendszus, M., & Biller, A. (2016) · NeuroImage

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 505

ChatGPT in healthcare: A taxonomy and systematic review

Li, J., Dada, A., Puladi, B., Kleesiek, J., & Egger, J. (2024) · Computer Methods and Programs in Biomedicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 452

Understanding metric-related pitfalls in image analysis validation

Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., et al. (2024) · Nature Methods

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 241

PSMA PET total tumor volume predicts outcome of patients with advanced prostate cancer receiving [177Lu]Lu-PSMA-617 radioligand therapy in a bicentric analysis

Seifert, R., Kessel, K., Schlack, K., Weber, M., Herrmann, K., Spanke, M., Fendler, W. P., Hadaschik, B., Kleesiek, J., Schäfers, M., et al. (2021) · European Journal of Nuclear Medicine and Molecular Imaging

Radiopharmaceutical Chemistry and ApplicationsMedical Imaging Techniques and Applications

Cited by 160

Common Limitations of Image Processing Metrics: A Picture Story

Reinke, A., Tizabi, M. D., Sudre, C. H., Eisenmann, M., Rädsch, T., Baumgartner, M., Acion, L., Antonelli, M., Arbel, T., Bakas, S., et al. (2021) · arXiv

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 126

DALSA: domain adaptation for supervised learning from sparsely annotated MR images

Goetz, M., Weber, C., Binczyk, F., Polanska, J., Tarnawski, R., Bobek-Billewicz, B., Koethe, U., Kleesiek, J., Stieltjes, B., & Maier-Hein, K. H. (2016) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 98

Medical large language models are susceptible to targeted misinformation attacks

Han, T., Nebelung, S., Khader, F., Wang, T., Müller-Franzes, G., Kuhl, C., Försch, S., Kleesiek, J., Haarburger, C., Bressem, K. K., et al. (2024) · npj Digital Medicine

Adversarial Robustness in Machine LearningArtificial Intelligence in Healthcare and Education

Cited by 62

Metrics reloaded: Recommendations for image analysis validation

Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M. D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., et al. (2022) · arXiv

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 59

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

Mese, I., D’Antonoli, T. A., Bluethgen, C., Bressem, K., Cuocolo, R., Chaudhari, A., Tejani, A. S., Isaac, A., Ponsiglione, A., Meddeb, A., et al. (2026) · Diagnostic and Interventional Radiology

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 17

Beyond Medical Imaging - A Review of Multimodal Deep Learning in Radiology

Heiliger, L., Sekuboyina, A., Menze, B., Egger, J., & Kleesiek, J. (2022)

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 13

Apple Vision Pro for Healthcare: "The Ultimate Display"? -- Entering the Wonderland of Precision Medicine

Egger, J., Gsaxner, C., Chen, X., Bian, J., Kleesiek, J., & Puladi, B. (2023) · arXiv

Augmented Reality ApplicationsVirtual Reality Applications and Impacts

Cited by 9

Fine-tuning BERT Models for Summarizing German Radiology Findings

Liang, S., Kades, K., Fink, M., Full, P., Weber, T., Kleesiek, J., Strube, M., & Maier-Hein, K. (2022) · Proceedings of the 4th Clinical Natural Language Processing Workshop

Topic ModelingMultimodal Machine Learning Applications

Cited by 8

Review of Disentanglement Approaches for Medical Applications: Towards Solving the Gordian Knot of Generative Models in Healthcare

Fragemann, J., Ardizzone, L., Egger, J., Kleesiek, J., & Workshop, M. (2022)

Generative Adversarial Networks and Image SynthesisExplainable Artificial Intelligence (XAI)

Cited by 6

A scoping review on the mental health harms of LLM-based chatbots

Diel, A., Torous, J., Cuijpers, P., Kleesiek, J., Nensa, F., Weber, N., Faust, F., Lalgi, T. J., Mellis, F. S., Teufel, M., et al. (2026) · npj Digital Medicine

Digital Mental Health InterventionsArtificial Intelligence in Healthcare and Education

Cited by 4