# DeepACSA
*Automatic analysis of human lower limb ultrasonography images*
DeepACSA is an open-source tool to evaluate the anatomical cross-sectional area of muscles in ultrasound images using deep learning.
More information about the installtion and usage of DeepACSA can be found in the online [documentation](https://deepacsa.readthedocs.io/en/latest/index.html). You can find information about contributing, issues and bug reports there as well.
If you find this work useful, please remember to cite the corresponding [paper](https://journals.lww.com/acsm-msse/Abstract/9900/DeepACSA__Automatic_Segmentation_of.87.aspx), where more information about the model architecture and performance can be found as well.
## Quickstart
To quickly start the DeepACSA either open the executable or type
``python -m Deep_ACSA``
in your prompt once the package was installed and the DeepACSA environment activated.
Raw data
{
"_id": null,
"home_page": "",
"name": "DeepACSA",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": "",
"keywords": "",
"author": "",
"author_email": "Paul Ritsche <paul.ritsche@unibas.ch>",
"download_url": "https://files.pythonhosted.org/packages/0b/15/ee38c9656e4383092777beee0dadcbcf491a46f94cb16dc8162f8e458ae6/deepacsa-0.3.1.tar.gz",
"platform": null,
"description": "# DeepACSA\n*Automatic analysis of human lower limb ultrasonography images*\n\nDeepACSA is an open-source tool to evaluate the anatomical cross-sectional area of muscles in ultrasound images using deep learning.\nMore information about the installtion and usage of DeepACSA can be found in the online [documentation](https://deepacsa.readthedocs.io/en/latest/index.html). You can find information about contributing, issues and bug reports there as well.\nIf you find this work useful, please remember to cite the corresponding [paper](https://journals.lww.com/acsm-msse/Abstract/9900/DeepACSA__Automatic_Segmentation_of.87.aspx), where more information about the model architecture and performance can be found as well. \n\n## Quickstart\n\nTo quickly start the DeepACSA either open the executable or type \n\n``python -m Deep_ACSA``\n\nin your prompt once the package was installed and the DeepACSA environment activated.\n",
"bugtrack_url": null,
"license": "",
"summary": "Automatic analysis of transversal muscle ultrasonography images",
"version": "0.3.1",
"project_urls": {
"Bug Tracker": "https://github.com/PaulRitsche/DeepACSA/issues",
"Homepage": "https://github.com/PaulRitsche/DeepACSA"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "69eafc5febd083abbcf455c75f2917f8e5fae59f9e868055f1bcd6c664ffb12b",
"md5": "d00aed09c5d67cde183441e78337b112",
"sha256": "68ca563007681750cbcdf20cf3aef0deed4f55f164049e57705afb0ec55629a1"
},
"downloads": -1,
"filename": "deepacsa-0.3.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "d00aed09c5d67cde183441e78337b112",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9",
"size": 50848,
"upload_time": "2023-10-08T18:46:47",
"upload_time_iso_8601": "2023-10-08T18:46:47.236798Z",
"url": "https://files.pythonhosted.org/packages/69/ea/fc5febd083abbcf455c75f2917f8e5fae59f9e868055f1bcd6c664ffb12b/deepacsa-0.3.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "0b15ee38c9656e4383092777beee0dadcbcf491a46f94cb16dc8162f8e458ae6",
"md5": "7fb9e6451fdc5e1b5b64cb990e31face",
"sha256": "161a2f42652a077e18f796691eae7747b4318c197a5ce7b28c676c9a4ffdbe5e"
},
"downloads": -1,
"filename": "deepacsa-0.3.1.tar.gz",
"has_sig": false,
"md5_digest": "7fb9e6451fdc5e1b5b64cb990e31face",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9",
"size": 81273,
"upload_time": "2023-10-08T18:46:49",
"upload_time_iso_8601": "2023-10-08T18:46:49.237398Z",
"url": "https://files.pythonhosted.org/packages/0b/15/ee38c9656e4383092777beee0dadcbcf491a46f94cb16dc8162f8e458ae6/deepacsa-0.3.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-10-08 18:46:49",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "PaulRitsche",
"github_project": "DeepACSA",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"requirements": [
{
"name": "jupyter",
"specs": [
[
"==",
"1.0.0"
]
]
},
{
"name": "Keras",
"specs": [
[
"==",
"2.9.0"
]
]
},
{
"name": "matplotlib",
"specs": [
[
"==",
"3.4.3"
]
]
},
{
"name": "numpy",
"specs": [
[
"==",
"1.21.2"
]
]
},
{
"name": "opencv-contrib-python",
"specs": [
[
"==",
"4.5.3.56"
]
]
},
{
"name": "pandas",
"specs": [
[
"==",
"1.3.3"
]
]
},
{
"name": "Pillow",
"specs": [
[
"==",
"8.3.2"
]
]
},
{
"name": "scikit-image",
"specs": [
[
"==",
"0.18.3"
]
]
},
{
"name": "scikit-learn",
"specs": [
[
"==",
"0.24.2"
]
]
},
{
"name": "tensorflow",
"specs": [
[
"==",
"2.9.0"
]
]
},
{
"name": "tqdm",
"specs": [
[
"==",
"4.62.3"
]
]
},
{
"name": "openpyxl",
"specs": [
[
"==",
"3.0.9"
]
]
},
{
"name": "h5py",
"specs": [
[
"==",
"3.4.0"
]
]
}
],
"lcname": "deepacsa"
}
JSON
