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Found 5 papers, 5 papers with code
Differentiable Voxel-based X-ray Rendering Improves Sparse-View 3D CBCT Reconstruction
We present DiffVox, a self-supervised framework for Cone-Beam Computed Tomography (CBCT) reconstruction by directly optimizing a voxelgrid representation using physics-based differentiable X-ray rendering.
Grad-CAMO: Learning Interpretable Single-Cell Morphological Profiles from 3D Cell Painting Images
Despite their black-box nature, deep learning models are extensively used in image-based drug discovery to extract feature vectors from single cells in microscopy images.
Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering
Preoperatively, a CNN is trained to regress the pose of a randomly oriented synthetic X-ray rendered from the preoperative CT.
Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative Imaging
To make DRRs interoperable with gradient-based optimization and deep learning frameworks, we have reformulated Siddon's method, the most popular ray-tracing algorithm used in DRR generation, as a series of vectorized tensor operations.
Multiscale Comparative Connectomics
The connectome, a map of the structural and/or functional connections in the brain, provides a complex representation of the neurobiological phenotypes on which it supervenes.
