Crate mikan

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§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.

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.

Re-exports§

pub use api::all;
pub use api::metrics;
pub use api::Evaluator;

Modules§

api: Core APIs. Carefully designed to be simple and easy to use.

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