Consensus ADMM for Inverse Problems Governed by Multiple PDE Models. - Luke Lozenski; Umberto Villa (CoRR, 2021)

A Memory-Efficient Self-Supervised Dynamic Image Reconstruction Method Using Neural Fields. - Luke Lozenski; Mark A. Anastasio; Umberto Villa (IEEE Trans. Computational Imaging, 2022)

Technical Note: PDE-constrained Optimization Formulation for Tumor Growth Model Calibration. - Baoshan Liang; Luke Lozenski; Umberto Villa; Danial Faghihi (CoRR, 2023)

Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth. - Baoshan Liang; Jingye Tan; Luke Lozenski; David A. Hormuth; Thomas E. Yankeelov; Umberto Villa; Danial Faghihi (IEEE Trans. Medical Imaging, 2023)

ProxNF: Neural Field Proximal Training for High-Resolution 4D Dynamic Image Reconstruction. - Luke Lozenski; Refik Mert Çam; Mark D. Pagel; Mark A. Anastasio; Umberto Villa (IEEE Trans. Computational Imaging, 2024)

Learned Full Waveform Inversion Incorporating Task Information for Ultrasound Computed Tomography. - Luke Lozenski; Hanchen Wang 003; Fu Li; Mark A. Anastasio; Brendt Wohlberg; Youzuo Lin; Umberto Villa (IEEE Trans. Computational Imaging, 2024)