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Found 4 papers, 2 papers with code
BMapOpt: Optimization of Brain Tissue Probability Maps using a Differentiable MRI Simulator
Reconstructing digital brain phantoms in the form of multi-channeled brain tissue probability maps for individual subjects is essential for capturing brain anatomical variability, understanding neurological diseases, as well as for testing image processing methods.
GaSpCT: Gaussian Splatting for Novel CT Projection View Synthesis
Furthermore, we empirically observe reduced training time compared to neural network based image synthesis for sparse-view CT image reconstruction.
InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model
To address this issue, we propose a novel approach that leverages a state-of-the-art 3D brain generative model, the latent diffusion model (LDM) trained on UK BioBank, to increase the resolution of clinical MRI scans.
3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images
Image synthesis via Generative Adversarial Networks (GANs) of three-dimensional (3D) medical images has great potential that can be extended to many medical applications, such as, image enhancement and disease progression modeling.
