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update docs
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Tinggong committed Apr 19, 2024
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17 changes: 8 additions & 9 deletions README.md
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[![Build Status](https://github.com/Tinggong/Microstructure.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/Tinggong/Microstructure.jl/actions/workflows/CI.yml?query=branch%3Amain)

Microstructure.jl is a Julia toolbox aiming at fast and probabilistic microstructure imaging. It features flexible and extendable compartment modelling with diffusion MRI and combined diffusion-relaxometry MRI. Microstructure.jl is currently under testing and optimization. If you have any questions using it, please email me at [email protected].
Microstructure.jl is a Julia toolbox designed for fast and probabilistic microstructure imaging. It offers flexible and extendable compartment modeling with diffusion MRI and combined diffusion-relaxometry MRI. The toolbox includes generic estimators such as Markov Chain Monte Carlo (MCMC) sampling methods and Monte Carlo dropout with neural networks. Microstructure.jl is currently undergoing testing and optimization. If you have any questions or encounter any issues while using it, please feel free to email me at [email protected].

## Installation
To install Microstructure.jl and keep up to date, you can use the repository link. Type ] in Julia to enter package mode and add the link:
To install Microstructure.jl, open Julia and enter the package mode by typing `]`, then add the package:

```julia
julia> ]
(@v1.8) pkg> add https://github.com/Tinggong/Microstructure.jl.git
(@v1.8) pkg> add Microstructrue
```

Once package registry is approved, you will be able to install it by using the package name:
Microstructure.jl is under active development and is frequently updated. To ensure you have the latest version, use the following command in the package mode:

```julia
(@v1.8) pkg> add Microstructrue
(@v1.8) pkg> up Microstructrue
```

## Usage
Documentation demonstrating different features of the package can be found on the [documentation website](https://tinggong.github.io/Microstructure.jl/dev/)
The documentation website is under construction and will be frequently updated.
## Usage
Documentation demonstrating various features of the package can be found on the [documentation website](https://tinggong.github.io/Microstructure.jl/dev/). Please note that the documentation website is currently under construction and will be frequently updated.

## Relationship to Other Packages
Microstructure.jl focuses on tissue microstructure estimation. If you are also interested in fiber orientation and tractography, please check out FreeSurfer.jl. Microstructure.jl also uses I/O functions from FreeSurfer.jl for reading and writing NIfTI image files.
Microstructure.jl focuses on tissue microstructure estimation. If you are also interested in fiber orientation and tractography, consider exploring FreeSurfer.jl. Additional, Microstructure.jl uses I/O functions from FreeSurfer.jl for reading and writing NIfTI image files.
2 changes: 1 addition & 1 deletion docs/src/getting_started.md
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# What is microstructure imaging?

Microstructure imaging allows us to estimate biologically meaningful cellular parameters from MRI data. This is achieved through simplifying the tissue in a voxel as multiple compartments representing different cellular structures, e.g. neurites and cell bodies etc. Each tissue compartment has unique features in determine the MR signals under a measurement protocol, and therefore can be estimated by solving an inverse problem.
Microstructure imaging allows us to estimate biologically meaningful cellular parameters from MRI data. This is achieved through simplifying the tissue in a voxel as multiple compartments representing different cellular structures, e.g. axons and cell bodies etc. Each tissue compartment has unique features in determine the MR signals under a measurement protocol, and therefore can be estimated by solving an inverse problem.

## Minimal steps
Here includes the minimal steps for you to get started with your MRI dataset. Visit tutorial and manual pages for more feature demonstrations.
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15 changes: 7 additions & 8 deletions docs/src/index.md
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Microstructure.jl is a Julia toolbox aiming at fast and probabilistic microstructure imaging. It supports flexible and extendable compartment modelling with diffusion MRI and combined diffusion-relaxometry MRI.

## Installation
To install Microstructure.jl, type ] in Julia to enter package mode and add the package
To install Microstructure.jl, type ] in Julia to enter package mode and add the package:

```julia
julia> ]
(@v1.8) pkg> add Microstructrue
```

or use github link to keep up to date:
Microstructure.jl is under active development and is frequently updated. To ensure you have the latest version, use the following command in the package mode:

```julia
(@v1.8) pkg> add https://github.com/Tinggong/Microstructure.jl.git
(@v1.8) pkg> up Microstructrue
```

## Feature Summary
- combined diffusion-relaxometry compartment modelling
- flexible in creating models and adjusting assumptions
- generic mcmc estimator
- parallel computing
- quality checking
- Combined diffusion-relaxometry compartment modelling
- Flexible in creating models and adjusting assumptions
- Generic MCMC and neural network estimators
- Parallel computing

## Relationship to Other Packages
Microstructure.jl focuses on tissue microstructure estimation. If you are also interested in fiber orientation and tractography, please check out FreeSurfer.jl. Microstructure.jl also uses I/O functions from FreeSurfer.jl for reading and writing mri image files.
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12 changes: 11 additions & 1 deletion docs/src/manual/multithreads.md
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# Multi threads

Constructing...
### Start julia in terminal with multi-threads
```terminal
~ % julia --threads auto
```
You can also set enviornment variable by adding `export JULIA_NUM_THREADS=auto` in your bash profile, which will use multi-threads automatically when you start julia.

### Multi-threads for MCMC estimation

```@docs
threading
```

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@JuliaRegistrator register

Release notes:

  • added multi-threads for MCMC estimation

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Registration pull request created: JuliaRegistries/General/105249

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.1.2 -m "<description of version>" 3fadf316a7973c2bf9b5dcb9df3999c321fc0935
git push origin v0.1.2

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