Rust library for reading/writing NIfTI-1 (nii.gz) files, with SimpleITK/NiBabel-like APIs, native Rust support, and Python bindings for cross-language performance.
If you have used SimpleITK/NiBabel, you will definitely love this and get started right away! 🕶
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🚀Pure Rust Implementation: Thanks to nifti-rs, I/O speed is comparable to SimpleITK and slightly faster than NiBabel.
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✨ Carefully Designed API: Super easy to use, with no learning curve; enjoy a consistent experience in Rust as in Python. Ideal for developers familiar with ITK-style libraries.
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🛠️Rust-Python bindings: Write heavy operations in Rust and easily call them in Python, combining the performance of Rust with the flexibility of Python.
For Rust projects, add the following to your Cargo.toml
:
[dependencies]
nii-rs = "*"
For Python, install via pip:
pip install nii-rs
To start developing with nii-rs, use the following command:
maturin dev -r
For details, please refer to the rust examples and python examples。
use nii;
// read image
let im = nii::read_image::<f32>("test.nii.gz");
// get attrs, style same as SimpleITK
let spacing: [f32; 3] = im.get_spacing();
let origin: [f32; 3] = im.get_origin();
let direction: [[f32; 3]; 3] = im.get_direction();
// get affine, style same as nibabel
let affine = im.get_affine();
// get array, style same as SimpleITK, i.e.: [z, y, x]
let arr: &Array3<f32> = im.ndarray();
// write image
nii::write_image(&im, "result.nii.gz")
import nii
# read image
im = nii.read_image("test.nii.gz")
# get attrs, style same as like SimpleITK
spacing = im.get_spacing()
origin = im.get_origin()
direction = im.get_direction()
# get affine, style same as nibabel
affine = im.get_affine()
# get array, style same as SimpleITK, i.e.: [z, y, x]
arr = im.ndarray()
# write image
nii.write_image(im, "result.nii.gz")
Licensed under either of the following licenses, at your choice:
Apache License, Version 2.0
(See LICENSE-APACHE or visit http://www.apache.org/licenses/LICENSE-2.0)
MIT License
(See LICENSE-MIT or visit http://opensource.org/licenses/MIT)
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project, as defined by the Apache License 2.0, will be dual-licensed under the above licenses without any additional terms or conditions.