Synthetic MRI

Synthetic MRI (sMRI) research focuses on generating realistic MRI images using artificial intelligence, primarily to address limitations of traditional MRI acquisition, such as cost, time, and potential risks associated with contrast agents. Current research employs various deep learning architectures, including Generative Adversarial Networks (GANs), diffusion models, and vision transformers, to synthesize images from different input modalities (e.g., other MRI sequences, CT scans, ultrasound) or even sparse data. This work holds significant promise for improving access to high-quality MRI data, enhancing diagnostic capabilities, and accelerating research in various medical fields by augmenting existing datasets and enabling novel applications like contrast-agent-free imaging.

Papers

October 23, 2024

Longitudinal Causal Image Synthesis
Yujia Li, Han Li, ans S. Kevin Zhou
Causal Graph Causal Model Counterfactual Image Longitudinal Image Synthetic MRI

October 14, 2024

Two-Stage Approach for Brain MR Image Synthesis: 2D Image Synthesis and 3D Refinement
Jihoon Cho, Seunghyuck Park, Jinah Park
Brain Tumor Segmentation Classification Task MRI Synthesis Two Stage Approach Synthetic MRI Image Intensity Shape Refinement Brain MRI Synthesis

September 27, 2024

Simulating Dynamic Tumor Contrast Enhancement in Breast MRI using Conditional Generative Adversarial Networks
Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou, Lidia Garrucho, Walter H.L. Pinaya, Daniel M. Lang, Julia A. Schnabel, Oliver Diaz, Karim Lekadir
Tumor Segmentation Conditional Generative Adversarial Network Non Contrast Breast MRI Synthetic MRI Dce Mri

September 3, 2024

T1-contrast Enhanced MRI Generation from Multi-parametric MRI for Glioma Patients with Latent Tumor Conditioning
Zach Eidex, Mojtaba Safari, Richard L.J. Qiu, David S. Yu, Hui-Kuo Shu, Hui Mao, Xiaofeng Yang
Glioblastoma Patient Multi Parametric MRI T1 Weighted Image Conditioning Synthetic MRI Contrast Enhanced Magnetic Resonance Imaging

April 30, 2024

X-Diffusion: Generating Detailed 3D MRI Volumes From a Single Image Using Cross-Sectional Diffusion Models
Emmanuelle Bourigault, Abdullah Hamdi, Amir Jamaludin
Diffusion Model Single Image Stable Diffusion Magnetic Resonance Synthetic MRI

November 21, 2023

HiFi-Syn: Hierarchical Granularity Discrimination for High-Fidelity Synthesis of MR Images with Structure Preservation
Ziqi Yu, Botao Zhao, Shengjie Zhang, Xiang Chen, Jianfeng Feng, Tingying Peng, Xiao-Yong Zhang
Structured Representation Multi Granularity Synthetic MRI Medical Image Translation Structure Preservation

October 31, 2023

Enhanced Synthetic MRI Generation from CT Scans Using CycleGAN with Feature Extraction
Saba Nikbakhsh, Lachin Naghashyar, Morteza Valizadeh, Mehdi Chehel Amirani
Feature Extraction Computed Tomography Image Registration CycleGAN Model Synthetic MRI Cycle Consistent Adversarial Network

October 11, 2023

BrainVoxGen: Deep learning framework for synthesis of Ultrasound to MRI
Shubham Singh, Dr. Mrunal Bewoor, Ammar Ranapurwala, Satyam Rai, Sheetal Patil
New Framework Magnetic Resonance Imaging Critical Synthesis MRI Volume Synthetic MRI 3D Ultrasound Neural Volume Rendering

October 7, 2023

Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs
Wei Peng, Tomas Bosschieter, Jiahong Ouyang, Robert Paul, Ehsan Adeli, Qingyu Zhao, Kilian M. Pohl
Generative Model Generative AI Generative AI Model Conditional Generative 3D Brain Synthetic MRI Synthetic Brain MRI

September 9, 2023

Video and Synthetic MRI Pre-training of 3D Vision Architectures for Neuroimage Analysis
Nikhil J. Dhinagar, Amit Singh, Saket Ozarkar, Ketaki Buwa, Sophia I. Thomopoulos, Conor Owens-Walton, Emily Laltoo, Yao-Liang Chen, Philip Cook, Corey McMillan, Chih-Chien Tsai, J-J Wang, Yih-Ru Wu, Paul M. Thompson
Convolutional Neural Network Deep Learning Model Transfer Learning Pre Trained Model Source Video Synthetic MRI Vision Architecture

June 5, 2023

Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion models
Muhammad Usman Akbar, Måns Larsson, Anders Eklund
Diffusion Model Generative Adversarial Network Consistent Comparison Brain Tumor Segmentation Synthetic Medical Image Synthetic MRI Progressive GAN

May 21, 2023

Generalizable synthetic MRI with physics-informed convolutional networks
Luuk Jacobs, Stefano Mandija, Hongyan Liu, Cornelis A. T. van den Berg, Alessandro Sbrizzi, Matteo Maspero
Magnetic Resonance Imaging Physic Informed Physic Informed Deep Learning Synthetic MRI Contrast Set

April 28, 2023

Cycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesis
Shaoyan Pan, Chih-Wei Chang, Junbo Peng, Jiahan Zhang, Richard L. J. Qiu, Tonghe Wang, Justin Roper, Tian Liu, Hui Mao, Xiaofeng Yang
Denoising Diffusion Probabilistic Model MRI Synthesis Synthetic MRI

July 11, 2022

Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease
Mehmet Saygın Seyfioğlu, Zixuan Liu, Pranav Kamath, Sadjyot Gangolli, Sheng Wang, Thomas Grabowski, Linda Shapiro
Data Detection Alzheimer'S Disease Common Disease Supervised Contrastive Learning Brain MRI 3D Brain Brain Like Synthetic MRI

June 1, 2022

Supervised Denoising of Diffusion-Weighted Magnetic Resonance Images Using a Convolutional Neural Network and Transfer Learning
Jakub Jurek, Andrzej Materka, Kamil Ludwisiak, Agata Majos, Kamil Gorczewski, Kamil Cepuch, Agata Zawadzka
Neural Network Convolutional Neural Network Transfer Learning Image Denoising Diffusion Weighted Synthetic MRI Echo Planar Imaging Supervised Denoising

February 20, 2022

A Novel Framework for Brain Tumor Detection Based on Convolutional Variational Generative Models
Wessam M. Salama, Ahmed Shokry
Novel Framework Brain Tumor Detection Synthetic MRI Variational Generative Model

November 15, 2021

Multimodal Generalized Zero Shot Learning for Gleason Grading using Self-Supervised Learning
Dwarikanath Mahapatra
Zero Shot Self Supervised Learning Histopathology Image Generalized Zero Shot Learning Synthetic MRI Gleason Grade

November 8, 2021

Synthetic magnetic resonance images for domain adaptation: Application to fetal brain tissue segmentation
Priscille de Dumast, Hamza Kebiri, Kelly Payette, Andras Jakab, Hélène Lajous, Meritxell Bach Cuadra
Domain Adaptation Application Proficiency Synthetic Data Fetal Brain Synthetic MRI Gray Matter

Synthetic MRI

Papers

Longitudinal Causal Image Synthesis

Two-Stage Approach for Brain MR Image Synthesis: 2D Image Synthesis and 3D Refinement

Simulating Dynamic Tumor Contrast Enhancement in Breast MRI using Conditional Generative Adversarial Networks

T1-contrast Enhanced MRI Generation from Multi-parametric MRI for Glioma Patients with Latent Tumor Conditioning

X-Diffusion: Generating Detailed 3D MRI Volumes From a Single Image Using Cross-Sectional Diffusion Models

HiFi-Syn: Hierarchical Granularity Discrimination for High-Fidelity Synthesis of MR Images with Structure Preservation

Enhanced Synthetic MRI Generation from CT Scans Using CycleGAN with Feature Extraction

BrainVoxGen: Deep learning framework for synthesis of Ultrasound to MRI

Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs

Video and Synthetic MRI Pre-training of 3D Vision Architectures for Neuroimage Analysis

Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion models

Generalizable synthetic MRI with physics-informed convolutional networks

Cycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesis

Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease

Supervised Denoising of Diffusion-Weighted Magnetic Resonance Images Using a Convolutional Neural Network and Transfer Learning

A Novel Framework for Brain Tumor Detection Based on Convolutional Variational Generative Models

Multimodal Generalized Zero Shot Learning for Gleason Grading using Self-Supervised Learning

Synthetic magnetic resonance images for domain adaptation: Application to fetal brain tissue segmentation