ct-reconstruction

"Structure-Aware Sparse-View X-ray 3D Reconstruction" (CVPR 2024) - A Toolbox for CT reconstruction and X-ray Novel View Synthesis

"Radiative Gaussian Splatting for Efficient X-ray Novel View Synthesis" (ECCV 2024)

"Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction" (NeurIPS 2024)

Awesome CT Reconstruction

"Neural Attenuation Fields for Sparse-View CBCT Reconstruction" (MICCAI 2022 Oral)

[WACV 2024] INCODE: Implicit Neural Conditioning with Prior Knowledge Embeddings

3D Cone beam CT reconstruction

Code for ICLR2026 paper - DM4CT: Benchmarking Diffusion Models for Computed Tomography Reconstruction

Matlab toolbox for polyenergetic quantitative (polyquant) X-ray CT reconstruction with demos.

[TMI 2026] DeepSparse: A Foundation Model for Sparse-View CBCT Reconstruction

Algebraic Reconstruction Technique (ART)

Code for TMLR paper "Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction"

The study works on generating CT images from MRI images, where unsupervised learning was used using VAE-CycleGan. Since the number of samples included in the data set used in the study, and therefore in this case we are in a state of epistemic uncertainty, therefore probabilistic models were used in forming the latent space.

Algebraic Reconstruction Technique (ART)

A PyTorch implementation of the data-driven convex regularization approach for inverse problems

Performing 3D Cone Beam CT Reconstruction on GPU

Tomography reconstruction Web App that keeps non-expert users in mind

Total Variation

ReCo-Diff: Residual-Conditioned Deterministic Sampling for Cold Diffusion in Sparse-View CT

Physics-aware cone-beam CT reconstruction from scratch using Python and PyTorch. Implements forward projection, analytical FDK, and classical iterative SIRT reconstruction with Apple Silicon (MPS) GPU support.