6 papers · 1 filter
Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
Cheng-Han Huang, Yongliang Sun, Chaoyan Huang +2
Many combinatorial optimization problems admit quadratic unconstrained binary formulations (QUBO) which can often be relaxed to the box and optimized using scalable gradi…
Trajectory Constraints for Imaging Inverse Problems
Chaoyan Huang, Haijie Yuan, Saiprasad Ravishankar +1
Diffusion models have achieved strong performance in imaging inverse problems, but typically rely on domain-matched pretrained models and external training data. Moreover, errors i…
A Principled Self-Referenced Early Stopping Approach for Deep Image Prior
Chaoyan Huang, Cheng-Han Huang, Ismail R. Alkhouri +1
Recently, Deep Image Prior (DIP) has demonstrated strong capabilities for solving inverse imaging problems (IIPs) by optimizing a randomly initialized convolutional neural network…
Fractional-gradient Sparsity with Autoencoding Sequential Deep Image Prior for 3D CT Reconstruction
Haijie Yuan, Chaoyan Huang, Srijita Bandopadhyay +2
3D volumetric reconstruction from incomplete or noisy measurements is a fundamental problem in medical imaging and computational tomography. Deep image prior (DIP)-based methods ha…
Dynamic MRI Reconstruction Via Dual Deep Priors and Low-Rank Plus Sparse Modeling
Yongliang Sun, Siddhant Gautam, Chaoyan Huang +3
Dynamic MRI reconstruction from undersampled measurements is a challenging inverse problem that requires preserving both spatial reconstruction quality and temporal consistency acr…
Frequency Error-Guided Under-sampling Optimization for Multi-Contrast MRI Reconstruction
Xinming Fang, Chaoyan Huang, Juncheng Li +3
Magnetic resonance imaging (MRI) plays a vital role in clinical diagnostics, yet it remains hindered by long acquisition times and motion artifacts. Multi-contrast MRI reconstructi…