https://github.com/stevenwhitaker/scandesign.jl
Optimal MRI scan design.
https://github.com/stevenwhitaker/scandesign.jl
Last synced: 5 months ago
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Optimal MRI scan design.
- Host: GitHub
- URL: https://github.com/stevenwhitaker/scandesign.jl
- Owner: StevenWhitaker
- Created: 2019-10-11T14:27:41.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-03-19T14:15:23.000Z (over 6 years ago)
- Last Synced: 2025-04-10T20:18:51.446Z (about 1 year ago)
- Language: Julia
- Size: 16.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# ScanDesign.jl
This package implements an MRI scan parameter optimization technique
presented in
[G. Nataraj, J.-F. Nielsen, and J. A. Fessler. Optimizing MR Scan Design for Model-Based T1, T2 Estimation from Steady-State Sequences. IEEE Trans. Med. Imag., 36(2):467-77, February 2017](https://ieeexplore.ieee.org/document/7582547).
This code was inspired by the MATLAB code written by Gopal Nataraj,
which can be found [here](https://github.com/gopal-nataraj/scn-dsgn).
## Getting Started
At the Julia REPL, type `]` to enter the package prompt.
Then type `add https://github.com/StevenWhitaker/ScanDesign.jl#v0.0.1`
to add ScanDesign v0.0.1
(note that `v0.0.1` can be replaced with whatever version is needed).
Hit backspace to return to the normal Julia prompt,
and then type `using ScanDesign` to load the package.
## Overview
The function `scandesign` provides the main functionality.
It takes as input an initial set of scan parameters
and a cost function to minimize
(as well as optional parameters for fine-grained control of the optimization).
The function `expectedcost` is the cost function used
in the paper mentioned above that takes an expectation
over a range of unknown and known parameters
of the trace of the inverse Fisher information matrix.
The function `fisher` computes the Fisher information matrix
as described in the aforementioned paper.