Prof. Dr. Bangti Jin

Research Areas

• Tikhonov-Phillips regularization
• Inverse problems

Theses (Selection)complete list

1. Electrical Impedance Tomography with the complete electrode model and sparsity constraints (Matthias Gehre)

Publications (Selection)complete list

1. R. Barbano, A. Denker, H. Chung, T. H. Roh, S. Arridge, P. Maaß, B. Jin, J. C. Ye.
   Steerable conditional diffusion for out-of-distribution adampation in medical image reconstruction.
   IEEE Transactions on Medical Imaging, 44(5), 2093:2104, 2025.

   DOI: 10.1109/TMI.2024.3524797

2. A. Denker, F. Margotti, J. Ning, K. Knudsen, D. Nganyu Tanyu, B. Jin, A. Hauptmann, P. Maaß.
   Deep Learning Based Reconstruction Methods for Electrical Impedance Tomography.
   Zur Veröffentlichung eingereicht.

   DOI: 10.48550/arXiv.2508.06281

3. R. Barbano, J. Antorán, J. Leuschner, J. M. Hernández-Lobato, B. Jin, Z. Kereta.
   Image Reconstruction via Deep Image Prior Subspaces.
   Zur Veröffentlichung eingereicht.

   online at: https://arxiv.org/abs/2302.10279

4. M. Nittscher, M. F. Lameter, R. Barbano, J. Leuschner, B. Jin, P. Maaß.
   SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction.
   Medical Imaging with Deep Learning (MIDL 2023), 10.07.-12.07.2023.
   

   online at: https://2023.midl.io/papers/p014

5. D. Nganyu Tanyu, J. Ning, A. Hauptmann, B. Jin, P. Maaß.
   Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches.
   Zur Veröffentlichung eingereicht.

   online at: https://arxiv.org/abs/2310.18636