Observed since 21 Oct, 11:13 UTC
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A library to convert Scanco AIM image files to numpy arrays and extract header information
aim2numpy is a Python library designed to convert AIM files, specifically CT scan data from Scanco, into numpy arrays.
You can install the library using pip:
pip install aim2numpy
Here's a basic example of how to use the library:
import aim2numpy
mynumpy = aim2numpy.extract("myaimfile.aim")
header_info = aim2numpy.get_header_info("myaimfile.aim")
The AIM file format is used by Scanco Medical for storing CT scan data. These files contain volumetric data that can be used for various analyses in medical imaging and research.
import aim2numpy
import matplotlib.pyplot as plt
# Extract the numpy array from the AIM file
ct_scan_data = aim2numpy.extract("myaimfile.aim")
# Display a slice of the CT scan data
plt.imshow(ct_scan_data[:, :, ct_scan_data.shape[2] // 2], cmap='gray')
plt.title('CT Scan Slice')
plt.show()
# Print header information
header_info = aim2numpy.get_header_info("myaimfile.aim")
print(f"Dimensions: {header_info['dimensions']}")
print(f"Element size: {header_info['element_size']} mm")
print(f"Processing log: {header_info['processing_log']}")
If you want to install the library for development purposes, you can clone the repository and install it locally:
git clone https://github.com/Alexhal9000/aim2numpy.git
cd aim2numpy
pip install -e .
To run the tests, use the following command:
python -m unittest discover tests
Contributions are welcome! Please open an issue or submit a pull request on GitHub.
This project is licensed under the MIT License. See the LICENSE file for details.
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.3.1 | 3 Sept 2025 | 0 |
This describes our collected data; it is not a security assessment.
Observed since 21 Oct, 11:13 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:202935f70ca13a3d33d5fe5efd91e4ccfb6d4c64d5a09b5cd1f24f8bb5e4cb6c