Disclaimer:
Not for commercial use.
This python package is currently a public beta release. You can use it free of charge for non-commercial applications until further notice. To use it, you still require a (free) license key, which you can get from the Python SDK product page. For commercial applications, please get in touch with us at info@imfusion.com.
Note also, the functionality offered here is only a subset of the Python bindings we have available. In particular, modality-specific plugins (e.g. for Ultrasound, CT, etc.) are not included. Please reach out to us if you are interested in such functionality or visit our webshop.
Overview
Description
The imfusion
package enables easy and fast loading, handling and processing of medical image data.
It is a wrapper around the ImFusion SDK and exposes a subset of its functionality to Python.
The major advantages of using imfusion
are:
High Performance:
Leveraging optimized C++ for fast execution and OpenGL for GPU acceleration, ensuring compatibility with various GPU vendors.
Versatile Data Structures:
Handle a wide range of medical images and data types, including 2D/3D images, metadata, deformations, rotations, masks, and segmentations. It also supports keypoints, point clouds, and meshes.
Extensive Set of Algorithms:
Access a vast array of image processing algorithms, from basic cropping to complex multi-modal image registration. Even algorithms that don’t have dedicated Python bindings can be executed through a functional interface.
File Format Support:
Load and save numerous medical imaging formats, including Nifti, MHD, Dicom, HDF5, PNG, and JPG and featuring a reliable Dicom loader used in FDA-approved products.
Deployment-Ready Data Pipelines:
Construct efficient data pipelines for ML model training and deployment, ensuring consistent pre-processing and post-processing.
numpy-like arithmetic but with images
Perform arithmetic operations on images with a functional API or operators, supporting GPU or CPU execution and, optionally, delayed expression evaluation for enhanced performance.
Documentation
Please find the documentation for this Python package at docs.imfusion.com/python.
Support
If you experience issues with this package, please let us know in our forum.
For business inquiries please contact info@imfusion.com.