MRI reconstruction (e.g., QSM) using deep learning methods

Last update: Dec 18, 2022

Overview

deepMRI: Deep learning methods for MRI

Authors: Yang Gao, Hongfu Sun

This repo is devloped based on Pytorch (1.8 or later) and matlab (R2019a or later).
The codes in this repo were tested on Centos 7.8 with Nvdia Tesla V100 and macos12.0.1/win10/ubuntu19.10 with GTX 1060

Projects

xQSM for QSM dipole inversion

DCRnet for QSM and R2* acceleration

iQSM for single-step instant QSM

xQSM for QSM dipole inversion

xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks

source code (github) | arXiv (pre-print) | NMR in Biomed (full paper)

DCRNet for QSM and R2* acceleration

Accelerating quantitative susceptibility and R2* mapping using incoherent undersampling and deep neural network reconstruction

source code (github) | arXiv (pre-print) | NeuroImage (full paper)

iQSM for single-step instant QSM

Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enabled deep neural networks

source code (github) | arXiv (pre-print)

⬆ top

MRI reconstruction (e.g., QSM) using deep learning methods

Related tags

Overview

deepMRI: Deep learning methods for MRI

Projects

xQSM for QSM dipole inversion

DCRNet for QSM and R2* acceleration

iQSM for single-step instant QSM

Owner

Hongfu Sun

[ICCV2021] Learning to Track Objects from Unlabeled Videos

Direct LiDAR Odometry: Fast Localization with Dense Point Clouds

A C implementation for creating 2D voronoi diagrams

Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation

Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017

PoseViz – Multi-person, multi-camera 3D human pose visualization tool built using Mayavi.

Code for the Shortformer model, from the paper by Ofir Press, Noah A. Smith and Mike Lewis.

The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"

FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning

The PyTorch implementation for paper "Neural Texture Extraction and Distribution for Controllable Person Image Synthesis" (CVPR2022 Oral)

Object detection on multiple datasets with an automatically learned unified label space.

Official PyTorch Implementation of paper "Deep 3D Mask Volume for View Synthesis of Dynamic Scenes", ICCV 2021.

Automatically download the cwru data set, and then divide it into training data set and test data set

FastyAPI is a Stack boilerplate optimised for heavy loads.

Pure python implementations of popular ML algorithms.

PolyGlot, a fuzzing framework for language processors

Simultaneous Demand Prediction and Planning

Data for "Driving the Herd: Search Engines as Content Influencers" paper

Self-Supervised Image Denoising via Iterative Data Refinement

This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.