Prof. Dr. Florian Knoll

Professur für Computational Imaging

Spatiotemporal variational neural network for reconstruction of highly accelerated cardiac cine MRI (2022) Vornehm M, Wetzl J, Giese D, Ahmad R, Knoll F Conference contribution, Abstract of a poster New-Generation Low-Field Magnetic Resonance Imaging of Hip Arthroplasty Implants Using Slice Encoding for Metal Artifact Correction: First in Vitro Experience at 0.55 T and Comparison with 1.5 T (2022) Khodarahmi I, Brinkmann IM, Lin DJ, Bruno M, Johnson PM, Knoll F, Keerthivasan MB, et al. Journal article Deep Learning Reconstruction Enables Highly Accelerated Biparametric MR Imaging of the Prostate (2022) Johnson PM, Tong A, Donthireddy A, Melamud K, Petrocelli R, Smereka P, Qian K, et al. Journal article Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications (2022) Zibetti MVW, Knoll F, Regatte RR Journal article Estimation of the capillary level input function for dynamic contrast-enhanced MRI of the breast using a deep learning approach (2022) Bae J, Huang Z, Knoll F, Geras K, Sood TP, Feng L, Heacock L, et al. Journal article Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction (2022) Narnhofer D, Effland A, Kobler E, Hammernik K, Knoll F, Pock T Journal article Virtual Mouse Brain Histology from Multi-contrast MRI via Deep Learning (2022) Liang Z, Lee CH, Arefin TM, Dong Z, Walczak P, Shi SH, Knoll F, et al. Journal article Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians (2021) Lin DJ, Johnson PM, Knoll F, Lui YW Journal article, Review article CG-SENSE revisited: Results from the first ISMRM reproducibility challenge (2021) Maier O, Baete SH, Fyrdahl A, Hammernik K, Harrevelt S, Kasper L, Karakuzu A, et al. Journal article, Review article Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge (2021) Johnson PM, Jeong G, Hammernik K, Schlemper J, Qin C, Duan J, Rueckert D, et al. Conference contribution