# Diffusion-Models-for-Medical-Imaging **Repository Path**: Heconnor/Diffusion-Models-for-Medical-Imaging ## Basic Information - **Project Name**: Diffusion-Models-for-Medical-Imaging - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-04-09 - **Last Updated**: 2025-04-09 ## Categories & Tags **Categories**: Uncategorized **Tags**: tutorial ## README # Diffusion-Models-for-Medical-Imaging Diffusion Models for Medical Imaging [**[Diffusion model in projection data (PPT)]**](https://github.com/yqx7150/EDAEPRec/tree/master/Slide) * Knowledge-driven deep learning for fast MR imaging: Undersampled MR image reconstruction from supervised to un-supervised learning [**[Paper]**](https://onlinelibrary.wiley.com/doi/10.1002/mrm.30105) * Deep learning for fast MR imaging: a review for learning reconstruction from incomplete k-space data [**[Paper]**](https://www.sciencedirect.com/science/article/abs/pii/S1746809421001762) * 基于扩散模型的医学成像研究综述 [**[Paper]**](https://www.cttacn.org.cn/article/doi/10.15953/j.ctta.2024.316) ## Learning from DAE to DSM
* Highly Undersampled Magnetic Resonance Imaging Reconstruction using Autoencoding Priors [**[Paper]**](https://cardiacmr.hms.harvard.edu/files/cardiacmr/files/liu2019.pdf) [**[Code]**](https://github.com/yqx7150/EDAEPRec) [**[Slide]**](https://github.com/yqx7150/EDAEPRec/tree/master/Slide) [**[数学图像联盟会议交流PPT]**](https://github.com/yqx7150/EDAEPRec/tree/master/Slide) * High-dimensional Embedding Network Derived Prior for Compressive Sensing MRI Reconstruction [**[Paper]**](https://www.sciencedirect.com/science/article/abs/pii/S1361841520300815?via%3Dihub) [**[Code]**](https://github.com/yqx7150/EDMSPRec) * Denoising Auto-encoding Priors in Undecimated Wavelet Domain for MR Image Reconstruction [**[Paper]**](https://www.sciencedirect.com/science/article/pii/S0925231221000990) [**[Paper]**](https://arxiv.org/ftp/arxiv/papers/1909/1909.01108.pdf) [**[Code]**](https://github.com/yqx7150/WDAEPRec) * REDAEP: Robust and Enhanced Denoising Autoencoding Prior for Sparse-View CT Reconstruction [**[Paper]**](https://ieeexplore.ieee.org/document/9076295) [**[Code]**](https://github.com/yqx7150/REDAEP) [**[PPT]**](https://github.com/yqx7150/HGGDP/tree/master/Slide) [**[数学图像联盟会议交流PPT]**](https://github.com/yqx7150/EDAEPRec/tree/master/Slide) * Accelerated model-based iterative reconstruction strategy for sparse-view photoacoustic tomography aided by multi-channel autoencoder priors [**[Paper]**](https://onlinelibrary.wiley.com/doi/10.1002/jbio.202300281) [**[Code]**](https://github.com/yqx7150/PAT-MDAE) * Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative Model [**[Paper]**](https://ieeexplore.ieee.org/abstract/document/9703672) [**[Code]**](https://github.com/yqx7150/EASEL) [**[PPT]**](https://github.com/yqx7150/HGGDP/tree/master/Slide) * Wavelet-improved Score-based Generative Model for Medical Imaging [**[Paper]**](https://ieeexplore.ieee.org/document/10288274) * 基于分数匹配生成模型的无透镜成像方法 [**[Paper]**](https://www.opticsjournal.net/Articles/OJf1842c2819a4fa2e/FigureTable) [**[Code]**](https://github.com/yqx7150/LSGM) [**[CIIS 2023-PPT]**](https://github.com/yqx7150/SHGM/tree/main) * Imaging through scattering media via generative diffusion model [**[Paper]**](https://pubs.aip.org/aip/apl/article/124/5/051101/3176612/Imaging-through-scattering-media-via-generative) [**[Code]**](https://github.com/yqx7150/ISDM) * Fluorescence molecular tomography via score-based generative model [**[Paper]**](https://www.sciencedirect.com/science/article/pii/S0143816625000508) [**[Code]**](https://github.com/yqx7150/FTSG) ## Learning from Image Domain to Projection Domain
* Homotopic Gradients of Generative Density Priors for MR Image Reconstruction [**[Paper]**](https://ieeexplore.ieee.org/abstract/document/9435335) [**[Code]**](https://github.com/yqx7150/HGGDP) [**[Slide]**](https://github.com/yqx7150/HGGDP/tree/master/Slide) * Universal Generative Modeling for Calibration-free Parallel MR Imaging [**[Paper]**](https://biomedicalimaging.org/2022/) [**[Code]**](https://github.com/yqx7150/UGM-PI) [**[Poster]**](https://github.com/yqx7150/UGM-PI/blob/main/paper%20%23160-Poster.pdf) * WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstruction [**[Paper]**](https://arxiv.org/abs/2205.03883) [**[Code]**](https://github.com/yqx7150/WKGM) [**[ISMRM_2022_slideliu6]**](https://github.com/yqx7150/WKGM/blob/main/ISMRM_2022_slideliu6.pdf) [**[ISMRM_2022_liu]**](https://submissions.mirasmart.com/ISMRM2022/Itinerary/ConferenceMatrixEventDetail.aspx?ses=WE-04) * Low-rank Tensor Assisted K-space Generative Model for Parallel Imaging Reconstruction [**[Paper]**](https://www.sciencedirect.com/science/article/abs/pii/S0730725X23001224) [**[Code]**](https://github.com/yqx7150/LR-KGM) * Universal Generative Modeling in Dual-domain for Dynamic MR Imaging [**[Paper]**](https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/abs/10.1002/nbm.5011) [**[Code]**](https://github.com/yqx7150/DD-UGM) * Physics-Informed DeepMRI: k-Space Interpolation Meets Heat Diffusion [**[Paper]**](https://ieeexplore.ieee.org/document/10683732) * Sub-DM: Subspace Diffusion Model with Orthogonal Decomposition for MRI Reconstruction [**[Paper]**](https://arxiv.org/pdf/2411.03758) * Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction [**[Paper]**](https://ieeexplore.ieee.org/document/10233041) [**[Code]**](https://github.com/yqx7150/GMSD) * Multi-phase FZA lensless imaging via diffusion model [**[Paper]**](https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-12-20595&id=531211) [**[Code]**](https://github.com/yqx7150/MLDM) [**[CIIS 2023-PPT]**](https://github.com/yqx7150/SHGM/tree/main) * Generative model for sparse photoacoustic tomography artifact removal [**[Paper]**](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12745/1274503/Generative-model-for-sparse-photoacoustic-tomography-artifact-removal/10.1117/12.2683128.short?SSO=1) * RED: Residual Estimation Diffusion for Low-Dose PET Sinogram Reconstruction [**[Paper]**](https://www.sciencedirect.com/science/article/pii/S1361841525001057) [**[Code]**](https://github.com/yqx7150/RED) * Sparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration [**[Paper]**](https://www.sciencedirect.com/science/article/pii/S2213597923001118) [**[Code]**](https://github.com/yqx7150/PAT-Diffusion) * High-resolution iterative reconstruction at extremely low sampling rate for Fourier single-pixel imaging via diffusion model [**[Paper]**](https://opg.optica.org/oe/fulltext.cfm?uri=oe-32-3-3138&id=545621) [**[Code]**](https://github.com/yqx7150/FSPI-DM) ## Learning from Large to Small Dataset
* One-shot Generative Prior in Hankel-k-space for Parallel Imaging Reconstruction [**[Paper]**](https://ieeexplore.ieee.org/document/10158730) [**[Code]**](https://github.com/yqx7150/HKGM) [**[PPT]**](https://github.com/yqx7150/HKGM/tree/main/PPT) * One Sample Diffusion Model in Projection Domain for Low-Dose CT Imaging [**[Paper]**](https://ieeexplore.ieee.org/abstract/document/10506793) [**[Code]**](https://github.com/yqx7150/OSDM) * Low-rank Angular Prior Guided Multi-diffusion Model for Few-shot Low-dose CT Reconstruction [**[Paper]**](https://ieeexplore.ieee.org/abstract/document/10776993) [**[Code]**](https://github.com/yqx7150/PHD) * Generative Modeling in Structural-Hankel Domain for Color Image Inpainting [**[Paper]**](http://arxiv.org/abs/2211.13857) [**[Code]**](https://github.com/yqx7150/SHGM) [**[CIIS 2023-PPT]**](https://github.com/yqx7150/SHGM/tree/main) ## Learning from One to Multiple Models
* Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-view CT Reconstruction [**[Paper]**](https://ieeexplore.ieee.org/abstract/document/10403850) [**[Code]**](https://github.com/yqx7150/SWORD) * Dual-Domain Collaborative Diffusion Sampling for Multi-Source Stationary Computed Tomography Reconstruction [**[Paper]**](https://ieeexplore.ieee.org/document/10577271) [**[Code]**](https://github.com/lizrzr/DCDS-Dual-domain_Collaborative_Diffusion_Sampling) * Diffusion Model based on Generalized Map for Accelerated MRI [**[Paper]**](https://doi.org/10.1002/nbm.5232) [**[Code]**](https://github.com/yqx7150/GM-SDE) * MSDiff: Multi-Scale Diffusion Model for Ultra-Sparse View CT Reconstruction [**[Paper]**](https://arxiv.org/pdf/2405.05763) [**[Code]**](https://github.com/yqx7150/MSDiff) * Multiple diffusion models-enhanced extremely limited-view reconstruction strategy for photoacoustic tomography boosted by multi-scale priors [**[Paper]**](https://www.sciencedirect.com/science/article/pii/S2213597924000636) [**[Code]**](https://github.com/yqx7150/MSDM-PAT) ## Learning from Regular to Irregular Samples
* Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstruction [**[Paper]**](https://arxiv.org/abs/2309.00853) [**[Code]**](https://github.com/yqx7150/CM-DM) * DP-MDM: Detail-Preserving MR Reconstruction via Multiple Diffusion Models [**[Paper]**](http://arxiv.org/abs/2211.13857) [**[Code]**](https://github.com/yqx7150/DP-MDM) * MSDiff: Multi-Scale Diffusion Model for Ultra-Sparse View CT Reconstruction [**[Paper]**](https://arxiv.org/pdf/2405.05763) [**[Code]**](https://github.com/yqx7150/MSDiff) * Diffusion Transformer Meets Random Masks: An Advanced PET Reconstruction Framework [**[Paper]**](https://arxiv.org/pdf/2503.08339) [**[Code]**](https://github.com/yqx7150/DREAM) * Physics-informed DeepCT: Sinogram Wavelet Decomposition Meets Masked Diffusion [**[Paper]**](https://arxiv.org/abs/2501.09935) [**[Code]**](https://github.com/yqx7150/SWARM)