Massively parallel Monte Carlo diffusion MR simulator written in Python.

Related tags

Deep Learningcudamonte-carlo-simulationgpu-computingdiffusion-mridiffusion-mri-simulation
Overview

Disimpy

Disimpy is a Python package for generating simulated diffusion-weighted MR signals that can be useful in the development and validation of data acquisition and analysis methods. The data is generated by Monte Carlo random walk simulations that run in massively parallel on Nvidia CUDA-capable GPUs. If you use Disimpy in work that leads to a scientific publication, please cite [1], where the details about signal generation can also be found.

Requirements and installation

Follow the installation instructions.

Usage example

Read the tutorial to learn how to use Disimpy.

Validation

Disimpy's functionality has been validated by comparing its results to analytical solutions and to results from other simulators (e.g., Camino and MISST), and by automated testing (disimpy.tests). Examples of simulations used for validation are provided here. However, Disimpy is research software and some bugs undoubtedly remain. If you find any of them or encounter unexpected behaviour, please open an issue on GitHub.

Contribute

If you want to contribute to the development of Disimpy, start by reading the contributing guidelines.

Support

If you have questions or need help, open an issue on Github.

References

[1] Kerkelä et al., (2020). Disimpy: A massively parallel Monte Carlo simulator for generating diffusion-weighted MRI data in Python. Journal of Open Source Software, 5(52), 2527. https://doi.org/10.21105/joss.02527
Owner
Leevi
Scientist and Python developer
Leevi
GitHub Repository https://disimpy.readthedocs.io/
DvD-TD3: Diversity via Determinants for TD3 version

DvD-TD3: Diversity via Determinants for TD3 version The implementation of paper Effective Diversity in Population Based Reinforcement Learning. Instal

3 Feb 11, 2022
EEGEyeNet is benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty

Introduction EEGEyeNet EEGEyeNet is a benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty. Overview T

Ard Kastrati 23 Dec 22, 2022
The official repo for OC-SORT: Observation-Centric SORT on video Multi-Object Tracking. OC-SORT is simple, online and robust to occlusion/non-linear motion.

OC-SORT Observation-Centric SORT (OC-SORT) is a pure motion-model-based multi-object tracker. It aims to improve tracking robustness in crowded scenes

Jinkun Cao 325 Jan 05, 2023
Multi-Joint dynamics with Contact. A general purpose physics simulator.

MuJoCo Physics MuJoCo stands for Multi-Joint dynamics with Contact. It is a general purpose physics engine that aims to facilitate research and develo

DeepMind 5.2k Jan 02, 2023
Personal project about genus-0 meshes, spherical harmonics and a cow

How to transform a cow into spherical harmonics ? Spot the cow, from Keenan Crane's blog Context In the field of Deep Learning, training on images or

3 Aug 22, 2022
Source code for the plant extraction workflow introduced in the paper “Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision”

Plant extraction workflow Source code for the plant extraction workflow introduced in the paper "Agricultural Plant Cataloging and Establishment of a

Maurice Günder 0 Apr 22, 2022
The 7th edition of NTIRE: New Trends in Image Restoration and Enhancement workshop will be held on June 2022 in conjunction with CVPR 2022.

NTIRE 2022 - Image Inpainting Challenge Important dates 2022.02.01: Release of train data (input and output images) and validation data (only input) 2

Andrés Romero 37 Nov 27, 2022
Official implementation for the paper: "Multi-label Classification with Partial Annotations using Class-aware Selective Loss"

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

99 Dec 27, 2022
Official pytorch code for SSC-GAN: Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation(ICCV 2021)

SSC-GAN_repo Pytorch implementation for 'Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation'.PDF SSC-GAN:Sem

tyty 4 Aug 28, 2022
Lazy, a tool for running things in idle time

Lazy, a tool for running things in idle time Mostly used to stop CUDA ML model training from making my desktop unusable. Simply monitors keyboard/mous

N Shepperd 46 Nov 06, 2022
DeepAL: Deep Active Learning in Python

DeepAL: Deep Active Learning in Python Python implementations of the following active learning algorithms: Random Sampling Least Confidence [1] Margin

Kuan-Hao Huang 583 Jan 03, 2023
iBOT: Image BERT Pre-Training with Online Tokenizer

Image BERT Pre-Training with iBOT Official PyTorch implementation and pretrained models for paper iBOT: Image BERT Pre-Training with Online Tokenizer.

Bytedance Inc. 435 Jan 06, 2023
[ICCV'2021] "SSH: A Self-Supervised Framework for Image Harmonization", Yifan Jiang, He Zhang, Jianming Zhang, Yilin Wang, Zhe Lin, Kalyan Sunkavalli, Simon Chen, Sohrab Amirghodsi, Sarah Kong, Zhangyang Wang

SSH: A Self-Supervised Framework for Image Harmonization (ICCV 2021) code for SSH Representative Examples Main Pipeline RealHM DataSet Google Drive Pr

VITA 86 Dec 02, 2022
A python tutorial on bayesian modeling techniques (PyMC3)

Bayesian Modelling in Python Welcome to "Bayesian Modelling in Python" - a tutorial for those interested in learning how to apply bayesian modelling t

Mark Regan 2.4k Jan 06, 2023
Auto HMM: Automatic Discrete and Continous HMM including Model selection

Auto HMM: Automatic Discrete and Continous HMM including Model selection

Chess_champion 29 Dec 07, 2022
PiRank: Learning to Rank via Differentiable Sorting

PiRank: Learning to Rank via Differentiable Sorting This repository provides a reference implementation for learning PiRank-based models as described

54 Dec 17, 2022
Wordle-solver - Wordle answer generation program in python

🟨 Wordle Solver 🟩 Wordle answer generation program in python ✔️ Requirements U

Dahyun Kang 4 May 28, 2022
Object Detection and Multi-Object Tracking

Object Detection and Multi-Object Tracking

Bobby Chen 1.6k Jan 04, 2023
Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.

Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch

AI Summer 962 Dec 23, 2022
Machine learning notebooks in different subjects optimized to run in google collaboratory

Notebooks Name Description Category Link Training pix2pix This notebook shows a simple pipeline for training pix2pix on a simple dataset. Most of the

Zaid Alyafeai 363 Dec 06, 2022