Siddhant Gautam
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View article: Learning Scan-Adaptive MRI Undersampling Patterns with Pre-Optimized Mask Supervision
Learning Scan-Adaptive MRI Undersampling Patterns with Pre-Optimized Mask Supervision Open
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 convolutional neural network (CNN) based framework for learning und…
View article: UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights Open
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)) typically require large amounts of fully sampled (clean) trai…
View article: Learning robust features for scatter removal and reconstruction in dynamic ICF X-ray tomography
Learning robust features for scatter removal and reconstruction in dynamic ICF X-ray tomography Open
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 projections are corrupted by unknown sources of noise and s…
View article: Scan-Adaptive MRI Undersampling Using Neighbor-based Optimization (SUNO)
Scan-Adaptive MRI Undersampling Using Neighbor-based Optimization (SUNO) Open
Accelerated MRI involves collecting partial $k$-space measurements to reduce acquisition time, patient discomfort, and motion artifacts, and typically uses regular undersampling patterns or human-designed schemes. Recent works have studied…
View article: Learning Robust Features for Scatter Removal and Reconstruction in Dynamic ICF X-Ray Tomography
Learning Robust Features for Scatter Removal and Reconstruction in Dynamic ICF X-Ray Tomography Open
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 projections are corrupted by unknown sources of noise and s…
View article: Patient-Adaptive and Learned MRI Data Undersampling Using Neighborhood Clustering
Patient-Adaptive and Learned MRI Data Undersampling Using Neighborhood Clustering Open
There has been much recent interest in adapting undersampled trajectories in MRI based on training data. In this work, we propose a novel patient-adaptive MRI sampling algorithm based on grouping scans within a training set. Scan-adaptive …
View article: A Spectrum of Hemoglobinopathies and Thalassemia Trait Using HPLC: Hospital-Based Observational Study in Northern India
A Spectrum of Hemoglobinopathies and Thalassemia Trait Using HPLC: Hospital-Based Observational Study in Northern India Open