mikan-rs 🍊
A medical image kit for segmentation metrics evaluation, native Rust support, and Python bindings for cross-language performance.
🎨 Features
-
🚀 Blazingly Fast: Written in Rust with high parallelization; speeds are 10-100x faster than medpy (depends on the number of cores in your CPU), especially for Hausdorff distance calculations.
-
🎯 Simple: The API is so intuitive that you can start using it immediately while reading the documentation in just one minute!
-
🧮 Comprehensive Metrics: Easily to compute almost all of segmentation metrics, results are consistent with medpy:
-
Confusion Matrix Based:
- Dice/IoU
- TP/TN/FP/FN
- Sensitivity/Specificity/Precision
- Accuracy/Balanced Accuracy
- ARI/FNR/FPR/F-score
- Volume Similarity
- MCC/nMCC/aMCC
-
Distance Based:
- Hausdorff Distance (HD)
- Hausdorff Distance 95 (HD95)
- Average Symmetric Surface Distance (ASSD)
- Mean Average Surface Distance (MASD)
-
🔨 Install
For Rust projects, add the following to your Cargo.toml:
[dependencies]
mikan-rs = "*"
For Python, install via pip:
pip install mikan-rs
🥒 Develop
maturin dev
📘 Usages
import mikan
import SimpleITK as sitk
gt = sitk.ReadImage("gt.nii.gz", sitk.sitkUInt8)
pred = sitk.ReadImage("pred.nii.gz", sitk.sitkUInt8)
e = mikan.Evaluator(gt, pred)
e.labels([1, 2, 3]).metrics(["dice", "hd", "hd95", "assd"])
For details, please refer to the python examples and rust examples.
🎄 Related Projects
- medpy: A well-known package for calculating segmentation metrics, with excellent documentation and implementation.
- miseval: A framework capable of calculating a large number of segmentation metrics.
- seg_metrics: A package for segmentation metrics that supports batch data calculation and CSV output, making it very convenient.
- MetricsReloaded: A new recommendation framework for biomedical image analysis validation, published in Nature Methods.
📃 Citation
If you use this software, we would appreciate it if you could include an mikan emoji 🍊 in your paper.
🍚 Q&A
Q: Why are my results different from seg_metrics/miseval/MetricsReloaded?
A: They are wrong. Of course, we might be wrong too. PRs to fix issues are welcome!
🔒 License
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.
Metadata
Release files for mikan-rs 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mikan_rs-0.1.4.tar.gz | 44.7 kB | Details |
Built distributions (wheels)
Total release size: 21.8 MB
Release files / mikan_rs-0.1.4.tar.gz
| Download URL | mikan_rs-0.1.4.tar.gz |
|---|---|
| Size | 44.7 kB |
| Tags | Source |
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Release files / mikan_rs-0.1.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
| Download URL | mikan_rs-0.1.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl |
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| Tags | Linux glibc 2.17+ x86-64 PyPy 3.10 PyPy 3.10 7.3 |
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| Download URL | mikan_rs-0.1.4-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl |
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Release files / mikan_rs-0.1.4-cp313-cp313-win_amd64.whl
| Download URL | mikan_rs-0.1.4-cp313-cp313-win_amd64.whl |
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| Size | 703.0 kB |
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| Download URL | mikan_rs-0.1.4-cp313-cp313-win32.whl |
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| Download URL | mikan_rs-0.1.4-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl |
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| Size | 654.0 kB |
| Tags | CPython 3.8 Windows x86-32 |
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Release files / mikan_rs-0.1.4-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
| Download URL | mikan_rs-0.1.4-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl |
|---|---|
| Size | 1.0 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ x86-32 |
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