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  • 2025

    Complex-Valued Federated Learning with Differential Privacy and MRI Applications

    Riess, A., Ziller, A., Kolek, S., Rueckert, D., Schnabel, J. & Kaissis, G., 2025, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops - ISIC 2024, iMIMIC 2024, EARTH 2024, DeCaF 2024, Held in Conjunction with MICCAI 2024, Proceedings. Celebi, M. E., Reyes, M., Chen, Z. & Li, X. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 191-203 13 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15274 LNCS).

    Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

  • Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound

    Mykula, H., Gasser, L., Lobmaier, S., Schnabel, J. A., Zimmer, V. & Bercea, C. I., 2025, Simplifying Medical Ultrasound - 5th International Workshop, ASMUS 2024, Held in Conjunction with MICCAI 2024, Proceedings. Gomez, A., Khanal, B., King, A. & Namburete, A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 220-230 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15186 LNCS).

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  • Enhancing the Utility of Privacy-Preserving Cancer Classification Using Synthetic Data

    Osuala, R., Lang, D. M., Riess, A., Kaissis, G., Szafranowska, Z., Skorupko, G., Diaz, O., Schnabel, J. A. & Lekadir, K., 2025, Artificial Intelligence and Imaging for Diagnostic and Treatment Challenges in Breast Care - 1st Deep Breast Workshop, Deep-Breath 2024, Held in Conjunction with MICCAI 2024, Proceedings. Mann, R. M., Zhang, T., Han, L., Litjens, G., Tan, T., Truhn, D., Li, S., Gao, Y., Doyle, S., Martí Marly, R., Kather, J. N., Pinker-Domenig, K. & Wu, S. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 54-64 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15451 LNCS).

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  • Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound

    Rasheed, H., Dorent, R., Fehrentz, M., Kapur, T., Wells, W. M., Golby, A., Frisken, S., Schnabel, J. A. & Haouchine, N., 2025, Simplifying Medical Ultrasound - 5th International Workshop, ASMUS 2024, Held in Conjunction with MICCAI 2024, Proceedings. Gomez, A., Khanal, B., King, A. & Namburete, A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 78-87 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15186 LNCS).

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  • MedEdit: Counterfactual Diffusion-Based Image Editing on Brain MRI

    Alaya, M. B., Lang, D. M., Wiestler, B., Schnabel, J. A. & Bercea, C. I., 2025, Simulation and Synthesis in Medical Imaging - 9th International Workshop, SASHIMI 2024, Held in Conjunction with MICCAI 2024, Proceedings. Fernandez, V., Wolterink, J. M., Wiesner, D., Remedios, S., Zuo, L. & Casamitjana, A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 167-176 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15187 LNCS).

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  • Non-parametric Neighborhood Test-Time Generalization: Application to Medical Image Classification

    Ambekar, S., Schnabel, J. A. & Lang, D. M., 2025, Medical Information Computing - First MICCAI Meets Africa Workshop, MImA 2024, and First MICCAI Student Board Workshop on Empowering Medical Information Computing and Research through Early-Career Expertise, EMERGE 2024, Held in Conjunction with MICCAI 2024, Revised Selected Papers. Anazodo, U., Akash, N., Fuchs, M., Cintas, C., Crimi, A., Mutsvangwa, T., Dako, F. & Ogallo, W. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 224-234 11 S. (Communications in Computer and Information Science; Band 2240).

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  • On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models

    Daum, D., Osuala, R., Riess, A., Kaissis, G., Schnabel, J. A. & Di Folco, M., 2025, Deep Generative Models - 4th MICCAI Workshop, DGM4MICCAI 2024, Held in Conjunction with MICCAI 2024, Proceedings. Mukhopadhyay, A., Oksuz, I., Engelhardt, S., Mehrof, D. & Yuan, Y. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 139-149 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15224 LNCS).

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  • Unsupervised Analysis of Alzheimer’s Disease Signatures Using 3D Deformable Autoencoders

    Avci, M. Y., Chan, E., Zimmer, V., Rueckert, D., Wiestler, B., Schnabel, J. A. & Bercea, C. I., 2025, Medical Information Computing - First MICCAI Meets Africa Workshop, MImA 2024, and First MICCAI Student Board Workshop on Empowering Medical Information Computing and Research through Early-Career Expertise, EMERGE 2024, Held in Conjunction with MICCAI 2024, Revised Selected Papers. Anazodo, U., Akash, N., Fuchs, M., Cintas, C., Crimi, A., Mutsvangwa, T., Dako, F. & Ogallo, W. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 266-276 11 S. (Communications in Computer and Information Science; Band 2240).

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  • 2024

    Advancing Neonatal Care: A Deep Learning Approach for Non-Contact Heart Rate Monitoring

    Grafton, A., Castelblanco, A., Warnecke, J. M., Thomson, L., Schubert, B., Hilgendorff, A., Schnabel, J. A., Lasenby, J. & Beardsall, K., 2024, 2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024. Institute of Electrical and Electronics Engineers Inc., (2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024).

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  • A Self-supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer

    Machado, I. P., Reithmeir, A., Kogl, F., Rundo, L., Funingana, G., Reinius, M., Mungmeeprued, G., Gao, Z., McCague, C., Kerfoot, E., Woitek, R., Sala, E., Ou, Y., Brenton, J., Schnabel, J. & Crispin, M., 2024, Biomedical Image Registration - 11th International Workshop, WBIR 2024, Held in Conjunction with MICCAI 2024, Proceedings. Modat, M., Špiclin, Ž., Hering, A., Simpson, I., Bastiaansen, W. & Mok, T. C. W. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 295-307 13 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15249 LNCS).

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  • DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology

    Koch, V., Wagner, S. J., Kazeminia, S., Sancar, E., Hehr, M., Schnabel, J. A., Peng, T. & Marr, C., 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 - 27th International Conference, Proceedings. Linguraru, M. G., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K. & Schnabel, J. A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 520-530 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15012 LNCS).

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    1 Zitat (Scopus)
  • Evaluation of Randomized Input Sampling for Explanation (RISE) for 3D XAI - Proof of Concept for Black-Box Brain-Hemorrhage Classification

    Highton, J., Chong, Q. Z., Crawley, R., Schnabel, J. A. & Bhatia, K. K., 2024, Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023) - Medical Imaging and Computer-Aided Diagnosis. Su, R., Zhang, Y.-D. & Frangi, A. F. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 41-51 11 S. (Lecture Notes in Electrical Engineering; Band 1166 LNEE).

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    1 Zitat (Scopus)
  • General Vision Encoder Features as Guidance in Medical Image Registration

    Kögl, F., Reithmeir, A., Sideri-Lampretsa, V., Machado, I., Braren, R., Rueckert, D., Schnabel, J. A. & Zimmer, V. A., 2024, Biomedical Image Registration - 11th International Workshop, WBIR 2024, Held in Conjunction with MICCAI 2024, Proceedings. Modat, M., Špiclin, Ž., Hering, A., Simpson, I., Bastiaansen, W. & Mok, T. C. W. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 265-279 15 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15249 LNCS).

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  • ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space

    Spieker, V., Huang, W., Eichhorn, H., Stelter, J., Weiss, K., Zimmer, V. A., Braren, R. F., Karampinos, D. C., Hammernik, K. & Schnabel, J. A., 2024, Deep Generative Models - Third MICCAI Workshop, DGM4MICCAI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Mukhopadhyay, A., Oksuz, I., Engelhardt, S., Zhu, D. & Yuan, Y. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 183-192 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14533 LNCS).

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    2 Zitate (Scopus)
  • Influence of Prompting Strategies on Segment Anything Model (SAM) for Short-axis Cardiac MRI Segmentation

    Stein, J., Di Folco, M. & Schnabel, J. A., 2024, Bildverarbeitung für die Medizin 2024 - Proceedings, German Conference on Medical Image Computing, 2024. Maier, A., Deserno, T. M., Handels, H., Maier-Hein, K., Palm, C. & Tolxdorff, T. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 54-59 6 S. (Informatik aktuell).

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    Open Access
  • Learning Physics-Inspired Regularization for Medical Image Registration with Hypernetworks

    Reithmeir, A., Schnabel, J. A. & Zimmer, V. A., 2024, Medical Imaging 2024: Image Processing. Colliot, O. & Mitra, J. (Hrsg.). SPIE, 129262K. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Band 12926).

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    Open Access
  • Low-Resource Finetuning of Foundation Models Beats State-of-the-Art in Histopathology

    Roth, B., Koch, V., Wagner, S. J., Schnabel, J. A., Marr, C. & Peng, T., 2024, IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings. IEEE Computer Society, (Proceedings - International Symposium on Biomedical Imaging).

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  • Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI

    Eichhorn, H., Spieker, V., Hammernik, K., Saks, E., Weiss, K., Preibisch, C. & Schnabel, J. A., 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 - 27th International Conference, Proceedings. Linguraru, M. G., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K. & Schnabel, J. A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 562-571 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15007 LNCS).

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  • Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks

    Fischer, S. M., Felsner, L., Osuala, R., Kiechle, J., Lang, D. M., Peeken, J. C. & Schnabel, J. A., 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, 27th International Conference Proceedings. Linguraru, M. G., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K. & Schnabel, J. A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 510-520 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15009 LNCS).

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    1 Zitat (Scopus)
  • Segmentation-guided Medical Image Registration: Quality Awareness using Label Noise Correctionn

    Raveendran, V., Spieker, V., Braren, R. F., Karampinos, D. C., Zimmer, V. A. & Schnabel, J. A., 2024, Bildverarbeitung für die Medizin 2024 - Proceedings, German Conference on Medical Image Computing, 2024. Maier, A., Deserno, T. M., Handels, H., Maier-Hein, K., Palm, C. & Tolxdorff, T. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 33-38 6 S. (Informatik aktuell).

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    2 Zitate (Scopus)
  • Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations

    Spieker, V., Eichhorn, H., Stelter, J. K., Huang, W., Braren, R. F., Rueckert, D., Sahli Costabal, F., Hammernik, K., Prieto, C., Karampinos, D. C. & Schnabel, J. A., 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 - 27th International Conference, Proceedings. Linguraru, M. G., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K. & Schnabel, J. A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 614-624 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15007 LNCS).

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  • Sparse Annotation Strategies for Segmentation of Short Axis Cardiac MRI

    Stein, J., Di Folco, M. & Schnabel, J. A., 2024, Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 14th International Workshop, STACOM 2023, Held in Conjunction with MICCAI 2023, Revised Selected Papers. Camara, O., Puyol-Antón, E., Suinesiaputra, A., Young, A., Sermesant, M., Tao, Q. & Wang, C. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 66-76 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14507 LNCS).

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  • Towards Generalised Neural Implicit Representations for Image Registration

    Zimmer, V. A., Hammernik, K., Sideri-Lampretsa, V., Huang, W., Reithmeir, A., Rueckert, D. & Schnabel, J. A., 2024, Deep Generative Models - Third MICCAI Workshop, DGM4MICCAI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Mukhopadhyay, A., Oksuz, I., Engelhardt, S., Zhu, D. & Yuan, Y. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 45-55 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14533 LNCS).

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  • Towards Learning Contrast Kinetics with Multi-condition Latent Diffusion Models

    Osuala, R., Lang, D. M., Verma, P., Joshi, S., Tsirikoglou, A., Skorupko, G., Kushibar, K., Garrucho, L., Pinaya, W. H. L., Diaz, O., Schnabel, J. A. & Lekadir, K., 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 - 27th International Conference, Proceedings. Linguraru, M. G., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K. & Schnabel, J. A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 713-723 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 15005 LNCS).

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  • 2023

    A skeletonization algorithm for gradient-based optimization

    Menten, M. J., Paetzold, J. C., Zimmer, V. A., Shit, S., Ezhov, I., Holland, R., Probst, M., Schnabel, J. A. & Rueckert, D., 2023, Proceedings - 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023. Institute of Electrical and Electronics Engineers Inc., S. 21337-21346 10 S. (Proceedings of the IEEE International Conference on Computer Vision).

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    7 Zitate (Scopus)
  • Bias in Unsupervised Anomaly Detection in Brain MRI

    Bercea, C. I., Puyol-Antón, E., Wiestler, B., Rueckert, D., Schnabel, J. A. & King, A. P., 2023, Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging - 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023, Proceedings. Wesarg, S., Oyarzun Laura, C., Puyol Antón, E., King, A. P., Baxter, J. S. H., Erdt, M., Drechsler, K., Freiman, M., Chen, Y., Rekik, I., Eagleson, R., Feragen, A., Cheplygina, V., Ganz-Benjaminsen, M., Ferrante, E., Glocker, B., Moyer, D. & Petersen, E. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 122-131 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14242 LNCS).

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    1 Zitat (Scopus)
  • Colorimetric Sensor Reading and Illumination Correction via Multi-Task Deep-Learning

    Castelblanco, A., Matzeu, G., Ruggeri, E., Omenetto, F. G., Hilgendorff, A., Schnabel, J. A. & Schubert, B., 2023, 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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    1 Zitat (Scopus)
  • F2FD: Fourier Perturbations for Denoising Cryo-Electron Tomograms and Comparison to Established Approaches

    Maldonado, J. C., Lamm, L., Liu, Y., Liu, Y., Righetto, R. D., Schnabel, J. A. & Peng, T., 2023, 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. IEEE Computer Society, (Proceedings - International Symposium on Biomedical Imaging; Band 2023-April).

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    2 Zitate (Scopus)
  • Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI

    Lang, D. M., Schwartz, E., Bercea, C. I., Giryes, R. & Schnabel, J. A., 2023, Cancer Prevention Through Early Detection - 2nd International Workshop, CaPTion 2023, Held in Conjunction with MICCAI 2023, Proceedings. Ali, S., van der Sommen, F., van Eijnatten, M., Kolenbrander, I., Papież, B. W. & Jin, Y. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 55-67 13 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14295 LNCS).

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  • Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection

    Bercea, C. I., Wiestler, B., Rueckert, D. & Schnabel, J. A., 2023, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings. Greenspan, H., Greenspan, H., Madabhushi, A., Mousavi, P., Salcudean, S., Duncan, J., Syeda-Mahmood, T. & Taylor, R. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 293-303 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14224 LNCS).

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    Open Access
    5 Zitate (Scopus)
  • What Do AEs Learn? Challenging Common Assumptions in Unsupervised Anomaly Detection

    Bercea, C. I., Rueckert, D. & Schnabel, J. A., 2023, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings. Greenspan, H., Greenspan, H., Madabhushi, A., Mousavi, P., Salcudean, S., Duncan, J., Syeda-Mahmood, T. & Taylor, R. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 304-314 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14224 LNCS).

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    7 Zitate (Scopus)
  • 2022

    Anato-Functional Adaptive Regularisation for Deep Learned MR-Guided PET Reconstruction

    Corda-D'incan, G., Schnabel, J. A. & Reader, A. J., 2022, 2022 IEEE NSS/MIC RTSD - IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detector Conference. Institute of Electrical and Electronics Engineers Inc., (2022 IEEE NSS/MIC RTSD - IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detector Conference).

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  • Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging

    Chan, E., O’Hanlon, C., Marquez, C. A., Petalcorin, M., Mariscal-Harana, J., Gu, H., Kim, R. J., Judd, R. M., Chowienczyk, P., Schnabel, J. A., Razavi, R., King, A. P., Ruijsink, B. & Puyol-Antón, E., 2022, Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers - 13th International Workshop, STACOM 2022, Held in Conjunction with MICCAI 2022, Revised Selected Papers. Camara, O., Puyol-Antón, E., Suinesiaputra, A., Young, A., Qin, C., Sermesant, M. & Wang, S. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 101-111 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13593 LNCS).

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    Open Access
    2 Zitate (Scopus)
  • A variational Bayesian method for similarity learning in non-rigid image registration

    Grzech, D., Azampour, M. F., Glocker, B., Schnabel, J., Navab, N., Kainz, B. & Folgoc, L. L., 2022, Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022. IEEE Computer Society, S. 119-128 10 S. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Band 2022-June).

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    9 Zitate (Scopus)
  • Quality-Aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled K-Space Data

    Machado, I., Puyol-Antón, E., Hammernik, K., Cruz, G., Ugurlu, D., Ruijsink, B., Castelo-Branco, M., Young, A., Prieto, C., Schnabel, J. A. & King, A. P., 2022, Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge - 12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Revised Selected Papers. Puyol Antón, E., Young, A., Suinesiaputra, A., Pop, M., Martín-Isla, C., Sermesant, M., Camara, O. & Lekadir, K. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 12-20 9 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13131 LNCS).

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    Open Access
    2 Zitate (Scopus)
  • Single-Modality Supervised Joint PET-MR Image Reconstruction

    Corda-D'incan, G., Schnabel, J. A. & Reader, A. J., 2022, 2022 IEEE NSS/MIC RTSD - IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detector Conference. Institute of Electrical and Electronics Engineers Inc., (2022 IEEE NSS/MIC RTSD - IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detector Conference).

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    Open Access
  • The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images

    Ugurlu, D., Puyol-Antón, E., Ruijsink, B., Young, A., Machado, I., Hammernik, K., King, A. P. & Schnabel, J. A., 2022, Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge - 12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Revised Selected Papers. Puyol Antón, E., Young, A., Suinesiaputra, A., Pop, M., Martín-Isla, C., Sermesant, M., Camara, O. & Lekadir, K. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 57-65 9 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13131 LNCS).

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    Open Access
  • 2021

    AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-center LGE MRIs

    Li, L., Zimmer, V. A., Schnabel, J. A. & Zhuang, X., 2021, Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 - 24th International Conference, Proceedings. de Bruijne, M., de Bruijne, M., Cattin, P. C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y. & Essert, C. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 557-566 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12906 LNCS).

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    24 Zitate (Scopus)
  • Automatic Re-orientation of 3D Echocardiographic Images in Virtual Reality Using Deep Learning

    Munroe, L., Sajith, G., Lin, E., Bhattacharya, S., Pushparajah, K., Simpson, J., Schnabel, J. A., Wheeler, G., Gomez, A. & Deng, S., 2021, Medical Image Understanding and Analysis - 25th Annual Conference, MIUA 2021, Proceedings. Papież, B. W., Yaqub, M., Jiao, J., Namburete, A. I. & Noble, J. A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 177-188 12 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12722 LNCS).

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    1 Zitat (Scopus)
  • Comparison of classical machine learning deep learning to characterise fibrosis inflammation using quantitative MRI

    Chan, E., Kelly, M. & Schnabel, J. A., 13 Apr. 2021, 2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021. IEEE Computer Society, S. 729-732 4 S. 9433962. (Proceedings - International Symposium on Biomedical Imaging; Band 2021-April).

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    1 Zitat (Scopus)
  • Dense Syn-Net: Inter-Modal and Self-Guided Deep Learned PET-MR Reconstruction

    Corda-D'incan, G., Schnabel, J. A. & Reader, A. J., 2021, 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2021 and 28th International Symposium on Room-Temperature Semiconductor Detectors, RTSD 2022. Tomita, H. & Nakamura, T. (Hrsg.). Institute of Electrical and Electronics Engineers Inc., (2021 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2021 and 28th International Symposium on Room-Temperature Semiconductor Detectors, RTSD 2022).

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    3 Zitate (Scopus)
  • Patient-specific 3d cellular automata nodule growth synthesis in lung cancer without the need of external data

    Manzanera, O. E. M., Ellis, S., Baltatzis, V., Nair, A., Le Folgoc, L., Desai, S., Glocker, B. & Schnabel, J. A., 13 Apr. 2021, 2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021. IEEE Computer Society, S. 925-928 4 S. 9433893. (Proceedings - International Symposium on Biomedical Imaging; Band 2021-April).

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    2 Zitate (Scopus)
  • Random Style Transfer Based Domain Generalization Networks Integrating Shape and Spatial Information

    Li, L., Zimmer, V. A., Ding, W., Wu, F., Huang, L., Schnabel, J. A. & Zhuang, X., 2021, Statistical Atlases and Computational Models of the Heart. MandMs and EMIDEC Challenges - 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers. Puyol Anton, E., Pop, M., Sermesant, M., Campello, V., Lalande, A., Lekadir, K., Suinesiaputra, A., Camara, O. & Young, A. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 208-218 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12592 LNCS).

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    Open Access
    9 Zitate (Scopus)
  • Self-Guided and MR-Guided Deep-Learned Post-Reconstruction PET Processing

    Corda-D'incan, G., Schnabel, J. A. & Reader, A. J., 2021, 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2021 and 28th International Symposium on Room-Temperature Semiconductor Detectors, RTSD 2022. Tomita, H. & Nakamura, T. (Hrsg.). Institute of Electrical and Electronics Engineers Inc., (2021 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2021 and 28th International Symposium on Room-Temperature Semiconductor Detectors, RTSD 2022).

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  • The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data

    Baltatzis, V., Le Folgoc, L., Ellis, S., Manzanera, O. E. M., Bintsi, K. M., Nair, A., Desai, S., Glocker, B. & Schnabel, J. A., 2021, Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data - 4th International Workshop, iMIMIC 2021, and 1st International Workshop, TDA4MedicalData 2021, Held in Conjunction with MICCAI 2021, Proceedings. Reyes, M., Henriques Abreu, P., Cardoso, J., Hajij, M., Zamzmi, G., Rahul, P. & Thakur, L. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 56-64 9 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12929 LNCS).

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    Open Access
    1 Zitat (Scopus)
  • The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification

    Baltatzis, V., Bintsi, K. M., Folgoc, L. L., Martinez Manzanera, O. E., Ellis, S., Nair, A., Desai, S., Glocker, B. & Schnabel, J. A., 2021, Predictive Intelligence in Medicine - 4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Proceedings. Rekik, I., Adeli, E., Park, S. H. & Schnabel, J. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 201-211 11 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12928 LNCS).

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    Open Access
    4 Zitate (Scopus)
  • 2020

    A Multi-task Approach Using Positional Information for Ultrasound Placenta Segmentation

    Zimmer, V. A., Gomez, A., Skelton, E., Ghavami, N., Wright, R., Li, L., Matthew, J., Hajnal, J. V. & Schnabel, J. A., 2020, Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis - 1st International Workshop, ASMUS 2020, and 5th International Workshop, PIPPI 2020, Held in Conjunction with MICCAI 2020, Proceedings. Hu, Y., Licandro, R., Noble, J. A., Hutter, J., Melbourne, A., Aylward, S., Abaci Turk, E., Torrents Barrena, J. & Torrents Barrena, J. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 264-273 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12437 LNCS).

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    12 Zitate (Scopus)
  • Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time

    Magnetti, C., Zimmer, V., Ghavami, N., Skelton, E., Matthew, J., Lloyd, K., Hajnal, J., Schnabel, J. A. & Gomez, A., 2020, Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings. Papiez, B. W., Namburete, A. I. L., Yaqub, M., Noble, J. A. & Yaqub, M. (Hrsg.). Springer, S. 423-435 13 S. (Communications in Computer and Information Science; Band 1248 CCIS).

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    Open Access
    1 Zitat (Scopus)
  • Iteration-Dependent Networks and Losses for Unrolled deep Learned FBSEM PET Image Reconstruction

    Corda-D'Incan, G., Schnabel, J. A. & Reader, A. J., 2020, 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020. Institute of Electrical and Electronics Engineers Inc., (2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020).

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    2 Zitate (Scopus)
  • Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention

    Li, L., Weng, X., Schnabel, J. A. & Zhuang, X., 2020, Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. Martel, A. L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M. A., Zhou, S. K., Racoceanu, D. & Joskowicz, L. (Hrsg.). Springer Science and Business Media Deutschland GmbH, S. 118-127 10 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12264 LNCS).

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    Open Access
    18 Zitate (Scopus)