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CT Reconstruction

Papers

Showing 76100 of 235 papers

TitleStatusHype
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction0
Deep learning based low-dose synchrotron radiation CT reconstruction0
Deep learning based dictionary learning and tomographic image reconstruction0
A three-dimensional dual-domain deep network for high-pitch and sparse helical CT reconstruction0
Deep Learning Based Computed Tomography Whys and Wherefores0
Deep Inertia L_p Half-Quadratic Splitting Unrolling Network for Sparse View CT Reconstruction0
A Splitting-Based Iterative Algorithm for GPU-Accelerated Statistical Dual-Energy X-Ray CT Reconstruction0
Stable Optimization for Large Vision Model Based Deep Image Prior in Cone-Beam CT Reconstruction0
4D X-Ray CT Reconstruction using Multi-Slice Fusion0
Deep Back Projection for Sparse-View CT Reconstruction0
DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding0
Are Pixel-Wise Metrics Reliable for Sparse-View Computed Tomography Reconstruction?0
Data-iterative Optimization Score Model for Stable Ultra-Sparse-View CT Reconstruction0
A patient-specific approach for quantitative and automatic analysis of computed tomography images in lung disease: application to COVID-19 patients0
Adaptation to CT Reconstruction Kernels by Enforcing Cross-domain Feature Maps Consistency0
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images0
Parallel Diffusion Model-based Sparse-view Cone-beam Breast CT0
A New Weighting Scheme for Fan-beam and Circle Cone-beam CT Reconstructions0
Gram filtering and sinogram interpolation for pixel-basis in parallel-beam X-ray CT reconstruction0
Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction0
CT sinogram-consistency learning for metal-induced beam hardening correction0
Geometric Constraints Enable Self-Supervised Sinogram Inpainting in Sparse-View Tomography0
CT-SDM: A Sampling Diffusion Model for Sparse-View CT Reconstruction across All Sampling Rates0
A Low-dose CT Reconstruction Network Based on TV-regularized OSEM Algorithm0
Active CT Reconstruction with a Learned Sampling Policy0
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