Welcome to Dosepy
Main documentation
Dosepy is an open-source Python library to perform radiochromic film dosimetry.
Dosepy is intended to be an accessible tool for medical physicists in radiation oncology to perform film dosimetry effortlessly.
Installation
Dosepy is distributed as a Python library under the Python Package Index (PyPI). Open a console (or 'terminal', or 'command prompt') and use the pip command:
pip install Dosepy
See the Python for Beginners getting started tutorial for an introduction to using your operating system’s console and interacting with Python.
Features
- Automatic film detection.
- Uncertainty analysis.
- Quality control test for error detection.
- Average of multiple scans for noise reduction.
- Handle lateral scanner response artifact.
Gamma index
Dose distributions comparison can be performed using the 2-dimensional gamma index test according to Low's definition Daniel_Low_gamma_1998, as well as some AAPM TG-218 Miften_TG218_2018 recommendations:
- The acceptance criteria for dose difference can be selected in absolute mode (in Gy) or relative mode (in %).
- In relative mode, the percentage could be interpreted with respect to the maximum dose (global normalization), or with respect to the local dose (local normalization); according to user selection.
- Dose threshold can be adjusted by the user.
- The reference distribution can be selected by the user.
- It is possible to define a search radius as an optimization process for calculation.
- By default, percentile 99 from dose distribution is used as maximum dose. This is used to avoid the possible inclusion of artifacts or user markers.
- Interpolation is not yet supported.
Used technologies
- Matplotlib for data visualization.
- Numpy for data array manipulation.
- PySide6 for graphical user interface (GUI).
- Pydicom to read files in DICOM format.
- Imageio to read files in TIFF format.
- Scikit-image and scipy for image processing.
Warning!
To use a software as a medical device, it is required to demonstrate its safety and efficacy through a risk categorization structure, a quality management system and a clinical evaluation; as described in the International Forum of Medical Device Regulators working group guidelines (IMDRF).
Dosepy is currently under development to meet quality standards. To achieve this in Mexico the regulatory mechanism is through NOM-241-SSA1-2021, in addition to the IMDRF guidelines.
Contributing
Dosepy uses GitHub as a platform to store and develop the software.
- To report software bugs, create an issue here
- To commit changes, create an issue, fork the repository, make your changes, and make a new pull request.
Discussion
Have questions? Ask them on the Dosepy discussion forum.
1 maintainer
Metadata
1 maintainer
Release files for Dosepy 0.12.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dosepy-0.12.2.tar.gz | 2.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dosepy-0.12.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.4 MB
Release files / dosepy-0.12.2.tar.gz
| Download URL | dosepy-0.12.2.tar.gz |
|---|---|
| Size | 2.2 MB |
| Tags | Source |
|
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No |
| Uploaded via |
twine/6.1.0 CPython/3.11.11
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Release files / dosepy-0.12.2-py3-none-any.whl
| Download URL | dosepy-0.12.2-py3-none-any.whl |
|---|---|
| Size | 2.2 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.11
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