X. Wu, J. Liu, H. Yu, A. Maier, Y. Huang, Self-Cascade Latent Schrödinger Bridge for CT Field-of-View Extension, Physics in Medicine and Biology. 2026
Z. Li, S. Ni, L. Yang, X. Yin, H. Yu, J. Wang, H. Han, W. Hu, Y. Huang. Efficient Image-to-Image Schrödinger Bridge for CT Field of View Extension. IEEE Transactions on Radiation and Plasma Medical Sciences. 2026
Y. Yuluo, K. Shen, Y. Ma, A. Wang, T. Jing, Y. Huang*, F. Wang*. GR-Gaussian: Graph-Based Radiative Gaussian Splatting for Sparse-View Tomographic Reconstruction. IEEE Transactions on Computational Imaging. 2026
Y. Huang, A. Maier, F. Fan, B. Kreher, X. Huang, R. Fietkau, H. Han, F. Putz, C. Bert. Learning Perspective Distortion Correction in Cone-Beam X-Ray Transmission Imaging. IEEE Transactions on Radiation and Plasma Medical Sciences. 2025
Publications Before AIMI
Y. Huang, Gomaa A, Hoefler D, Schubert P, Gaipl U, Frey B, Fietkau R, Bert C, Putz F. Principles of artificial intelligence in radiooncology. Strahlentherapie und Onkologie. 2025
Y. Huang, Z. Khodabakhshi, A.Gomaa, M. Schmidt, R. Fietkau, M. Guckenberger, N. Andratschke, C. Bert, S.Tanadini-Lang, F. Putz, “Multicenter privacy-preserving model training for deep learning brain metastases autosegmentation,” Radiotherapy and Oncology, 2024 (Radiation oncology top journal)
Y. Huang, C. Bert, A. Gomaa, R. Fietkau, A. Maier, F. Putz, “An experimental survey of incremental transfer learning for multicenter collaboration,” IEEE Access. 2024
Y. Huang, A. Gomaa, T. Weissmann, J. Grigo, H. Ben Tkhayat, B. Frey, U. Gaipl, L. Distel, A. Maier, R. Fietkau, C. Bert, F. Putz, “Benchmarking ChatGPT-4 on ACR radiation oncology in-training exam (TXIT): Potentials and challenges for AI-assisted medical education and decision making in radiation oncology.” Front. Oncol. 2023
Y. Huang, A. Preuhs, M. Manhart, G. Lauritsch, and A. Maier, “Data Extrapolation from Learned Prior Images for Truncation Correction in Computed Tomography,” IEEE Trans. Med. Imaging, 2021 (Medical imaging top journal)
Y. Huang, F. Fan, C. Syben, P. Roser, L. Mill, and A. Maier, “Cephalogram Synthesis and Landmark Detection in Dental Cone-Beam CT Systems,” Med. Image Anal. 2021 (Medical imaging top journal)
Y. Huang, S. Wang, Y. Guan, and A. Maier, “Limited Angle Tomography for Transmission X-Ray Microscopy Using Deep Learning,” J. Synchrotron Radiat. 2020
Hou Y, Bert C, Gomaa A, Lahmer G, Höfler D, Weissmann T, Voigt R, Schubert P, Schmitter C, Depardon A, Semrau S., A. Maier, F. Rainer, Y. Huang✉, F. Putz, Fine-tuning a local LLaMA-3 large language model for automated privacy-preserving physician letter generation in radiation oncology. Frontiers in Artificial Intelligence. 2025
F. Putz, M. Haderlein, S. Lettmaier, S. Semrau, R. Fietkau, Y. Huang✉, “Exploring the Capabilities and Limitations of Large Language Models for Radiation Oncology Decision Support”, International Journal of Radiation Oncology, Biology, Physics. 2024 (Radiation oncology top journal)
F. Fan, B. Kreher, H. Keil, A. Maier, and Y. Huang✉, “Fiducial Marker Recovery and Detection from Severely Truncated Data in Navigation Assisted Spine Surgery,” Med. Phys. 2022
B. Dutta, K. Root, I. Ullmann, F. Wagner, M. Mayr, M. Seuret, M. Thies, D. Stromer, V. Christlein, J. Schür, A. Maier, Y. Huang✉, “Deep Learning for Terahertz Image Denoising in Nondestructive Historical Document Analysis,” Sci. Rep. 2022
J. Chen*, H. Yu*, S. Ni, C. Liu, W. Ge, Y. Huang✉, and F. Liu✉. “Weighted filtered back-projection for source translation computed tomography reconstruction,” IEEE Trans. Instrum. Meas. 2023.
H. Yu, S. Ni, M. Thies, F. Wagner, Y. Huang✉, F. Liu✉, A. Maier, “Multiple source translation micro-CT improves both field-of-view and spatial resolution,” IEEE Trans. Instrum. Meas. 2024.
T. Weissmann, S. Mansoorian, M. S. May, S. Lettmaier, D. Höfler, L. Deloch, S. Speer, M. Balk, B. Frey, U. Gaipl, C. Bert, L. Distel, F. Walter, C. Belka, S. Semrau, H. Iro, R. Fietkau, Y. Huang✉, F. Putz✉, “Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design.” Cancers, 2023
A. Hagag, A. Gomaa, D. Kornek, A. Maier, R. Fietkau, C. Bert, Y. Huang✉, and F. Putz. “Deep Learning for Cancer Prognosis Prediction Using Portrait Photos by StyleGAN Embedding.” MICCAI 2024.
Y. Huang, A. Maier, R. Fietkau, C. Bert, and F. Putz, “Deep learning for perspective deformation correction in X-ray imaging,” European Society for Radiotherapy and Oncology (ESTRO), Vienna, Austria 2023
Y. Huang, C. Bert, P. Sommer, B. Frey, U. Gaipl, L. Distel, T. Weissmann, M. Uder, M. Schmidt, A. Dörfler, A. Maier, R. Fietkau, and F. Putz, “Improvement of Deep Learning-Based Auto-detection of Brain Metastases by Integrating prior MRI Images,”Strahlentherapie und Onkologie 2022. doi: 10.1007/s00066-022-01932-3 (Best Abstract Award in German Society of Radiation Oncology (DEGRO) conference)