6 papers
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…
Scan-Adaptive Dynamic MRI Undersampling Using a Dictionary of Efficiently Learned Patterns
Siddhant Gautam, Angqi Li, Prachi P. Agarwal +4
Cardiac MRI is limited by long acquisition times, which can lead to patient discomfort and motion artifacts. We aim to accelerate Cartesian dynamic cardiac MRI by learning efficien…
Scan-Adaptive MRI Undersampling Using Neighbor-based Optimization (SUNO)
Siddhant Gautam, Angqi Li, Nicole Seiberlich +2
Accelerated MRI involves collecting partial -space measurements to reduce acquisition time, patient discomfort, and motion artifacts, and typically uses regular undersampling pa…
Learning Scan-Adaptive MRI Undersampling Patterns with Pre-Optimized Mask Supervision
Aryan Dhar, Siddhant Gautam, Saiprasad Ravishankar
Deep learning techniques have gained considerable attention for their ability to accelerate MRI data acquisition while maintaining scan quality. In this work, we present a convolut…
Learning Robust Features for Scatter Removal and Reconstruction in Dynamic ICF X-Ray Tomography
Siddhant Gautam, Marc L. Klasky, Balasubramanya T. Nadiga +3
Density reconstruction from X-ray projections is an important problem in radiography with key applications in scientific and industrial X-ray computed tomography (CT). Often, such…
UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
Shijun Liang, Ismail R. Alkhouri, Siddhant Gautam +2
Recent advances in data-centric deep generative models have led to significant progress in solving inverse imaging problems. However, these models (e.g., diffusion models (DMs)) ty…