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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! 🕶

• 🚀Pure Rust Implementation: Thanks tonifti-rs, I/O speed is comparable to SimpleITK and slightly faster than NiBabel.

• ✨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.

• 🛠️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 yourCargo.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 therust examples andpython examples。

use nii;// read imagelet im = nii::read_image::<f32>("test.nii.gz");// get attrs, style same as SimpleITKlet 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 nibabellet affine = im.get_affine();// get array, style same as SimpleITK, i.e.: [z, y, x]let arr:&Array3<f32> = im.ndarray();// write imagenii::write_image(&im,"result.nii.gz")

importnii# read imageim=nii.read_image("test.nii.gz")# get attrs, style same as like SimpleITKspacing=im.get_spacing()origin=im.get_origin()direction=im.get_direction()# get affine, style same as nibabelaffine=im.get_affine()# get array, style same as SimpleITK, i.e.: [z, y, x]arr=im.ndarray()# write imagenii.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.