Skip to main content

patient specific anatomic coordinate system generation for shoulder bones

Project description

shoulder

PyPI Latest Release Code style: black

This package uses a collection of machine learning models to detect anatomic landmarks on 3d models of shoulder bones and also generates patient specific coordinate systems. An stl of the shoulder bone of interest is all that is needed to get started. Currently only implemented for the humerus, with expansion to the scapula in the future. Landmarks that shoulder can currently identify on the humerus are:

  • canal
  • transepicondylar axis
  • bicipital groove
  • anatomic neck

Installation

compatible with python 3.10 and 3.11

pip install shoulder

Example

Start by using the example bone stl's located in "tests/test_bones"

# pass stl into Humerus
hum = shoulder.Humerus("tests/test_bones/humerus_left.stl")

# apply coordinate sysytem
hum.apply_csys_canal_transepiconylar()

# calculate landmarks
hum.canal.axis()
hum.trans_epiconylar.axis()
hum.anatomic_neck.points()
hum.bicipital_groove.axis()

# calculate metrics
hum.radius_curvature()
hum.neckshaft()
hum.retroversion()

# construct plot from above humeral bone with landmarks and coordinate system
plot = shoulder.Plot(hum)
plot.figure.show()

The output of the plot will appear as shown below with landmarks included and transformed from the original CT coordinate system to a coordainte system defined by the canal and transepicondylar axis.

Plot of Example code above

Contributing

Clone the repo, open the cloned folder containing the poetry.lock file, then install the development dependencies using poetry.

poetry install --with dev

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

shoulder-1.3.0.tar.gz (38.9 MB view details)

Uploaded Source

Built Distribution

shoulder-1.3.0-py3-none-any.whl (38.9 MB view details)

Uploaded Python 3

File details

Details for the file shoulder-1.3.0.tar.gz.

File metadata

  • Download URL: shoulder-1.3.0.tar.gz
  • Upload date:
  • Size: 38.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.0 CPython/3.11.5 Linux/6.5.0-17-generic

File hashes

Hashes for shoulder-1.3.0.tar.gz
Algorithm Hash digest
SHA256 6cdbd03fd8e31313e1de6c6b2e6bc0265b8a638602ee2d9c9c8f6551bd25eeda
MD5 5da230869839df6e96ab2386ea2d94c3
BLAKE2b-256 507e7c3d005520873095b4714709cf756c4cec50462e9b75549545655a47014f

See more details on using hashes here.

File details

Details for the file shoulder-1.3.0-py3-none-any.whl.

File metadata

  • Download URL: shoulder-1.3.0-py3-none-any.whl
  • Upload date:
  • Size: 38.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.0 CPython/3.11.5 Linux/6.5.0-17-generic

File hashes

Hashes for shoulder-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b1ef6570946c8c0f5f8418e6eb2673708f4a514ebc67443bb99a112f2ce3b4c1
MD5 3a1fc8381c778626ecd6534b1bd4de03
BLAKE2b-256 f8ec912322a2c2f2bd61ee0e91492d87d8accc8c763f849e5fe30fad5bdd3a00

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page