Publications

Journal articles and conference contributions from AIMI and earlier research.

Publications at AIMI

2026

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

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

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

2025

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

2025

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

2024

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)

2024

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

2023

 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

2021

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)

2021

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)

2020

Y. Huang, S. Wang, Y. Guan, and A. Maier, “Limited Angle Tomography for Transmission X-Ray Microscopy Using Deep Learning,” J. Synchrotron Radiat. 2020

2025

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

2024

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)

2022

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

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

2023

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.

2024

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.

2023

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

2024

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.

2023

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

2022

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)

Search AIMI Lab

Search people, research, news and publications.

Image preview

Open original in new tab ↗