Skip to main content

zea logo

zea

A Toolbox for Cognitive Ultrasound Imaging

PyPI version Continuous integration Documentation Status License codecov status arXiv Hugging Face GitHub stars

Welcome to the zea package.

zea is a Python library that offers ultrasound signal processing, image reconstruction, and deep learning. Currently, zea offers:

  • A flexible ultrasound signal processing and image reconstruction Pipeline written in your favorite deep learning framework.
  • A complete set of Data loading tools for ultrasound data and acquisition parameters, designed for deep learning workflows.
  • A collection of pretrained Models for ultrasound image and signal processing.
  • A set of action selection functions for cognitive ultrasound in the Agent module.
  • Multi-Backend Support via Keras3: You can use PyTorch, TensorFlow, or JAX.

Check out the About page for more information and the motivation behind zea. For any questions or suggestions, please feel free to open an issue on GitHub. If you want to contribute, check out the Contributing guide.

Metadata

Release files for zea 0.1.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for zea 0.1.7
File Size Uploaded
zea-0.1.7.tar.gz 679.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for zea 0.1.7
File Interpreter ABI Platform
zea-0.1.7-py3-none-any.whl Python 3 none any Details

Total release size: 1.4 MB

Release files / zea-0.1.7.tar.gz

Download URL zea-0.1.7.tar.gz
Size 679.8 kB
Tags Source
SHA-256 checksum
How to use checksums
e61527ce58745ffd8f14f9f231eb45ad1c7e632957036c9dffbeebe6c28cdf40
BLAKE2b-256 checksum
How to use checksums
c3a92b2ebf7cb9bf709aaefb20932f0cc9377c2eb73db834fe591089145b6fd0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 21, 2026.

Transparency log

Release files / zea-0.1.7-py3-none-any.whl

Download URL zea-0.1.7-py3-none-any.whl
Size 747.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
be6f709363cc3770df1cef2d6967df8b240e999318a10a9c985e058585afc3f7
BLAKE2b-256 checksum
How to use checksums
e010a8f8cd2b892062d71219d16f145d12f491d22e7a87ece1af3e3c7bef9ade
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 21, 2026.

Transparency log
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page