Easy, robust registration of retinal images
Project description
retinalysis-registration
Easy, robust registration of retinal fundus images using classical computer vision: keypoint detection and SIFT matching. No GPU is required, and dependencies are lightweight (OpenCV, scikit-image, and related scientific Python packages).
The method achieves state-of-the-art performance on the FIRE dataset; see the FIRE evaluation notebook for details.
Installation
pip install retinalysis-registration
Dependencies
This package depends on retinalysis-fundusprep (>=1.1.0) for fundus bounds detection and cropping.
Usage
See the Example notebook for a minimal walkthrough.
Reference
Abstract presented at ARVO 2026: Investigative Ophthalmology & Visual Science.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file retinalysis_registration-1.0.0.tar.gz.
File metadata
- Download URL: retinalysis_registration-1.0.0.tar.gz
- Upload date:
- Size: 7.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4df17a67cb347c3e69ff6ddd0ef3515d5e7789f34e86776c58085da23e40c56e
|
|
| MD5 |
e9ad692117a4d6b1c4d53e4c84b7b2cd
|
|
| BLAKE2b-256 |
86cfaa9a56162dd5ff35ae9eac7279decb0d2e411791b15576ff7bdc8eba4be3
|
File details
Details for the file retinalysis_registration-1.0.0-py3-none-any.whl.
File metadata
- Download URL: retinalysis_registration-1.0.0-py3-none-any.whl
- Upload date:
- Size: 42.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a0c087daafb9d07f0497817d965c4a1ca3f9eb5ffaabda3f64dd466216f10108
|
|
| MD5 |
f463794c2631289a6a05158a199a9376
|
|
| BLAKE2b-256 |
9ec129fb729c2ff8ba758282437e5f74dd7036a7b13e7c0ccb9d0037cd2c8007
|
