ImFusion Labels is designed to ease the workflow of medical image annotation for further algorithm development. In particular, it provides a user-friendly way of managing a database of images and annotating them in a few clicks.
A free demo is available on our Download page. To get more information or to buy the full version, get in touch with us!
- Import all your images into a single project
- Smoothly browse and visualize all datasets with associated labels
- Search and sort your database with tags
- Use our smart algorithms to annotate images, volumes and sequences
- Import existing annotations
- Write your own interactive algorithms
- Refine the results with various post-processing tools
- Export your database directly for your training pipeline
- Choose the file format, encoding, resolution, etc.
- Add data augmentation to generate more images
- Try your algorithms on the whole dataset and compare results to the ground truth
Key advantages over existing solutions
- the support of a large variety of image modalities and data format, including DICOM images,
- a toolset of segmentation algorithms that have been designed to be as fast and intuitive as possible,
- a Python integration, which allows user to write their own algorithms to help them label data or run experiments on all existing ones,
- a powerful and customizable visualization of data and their labels,
- the possibility to easily define post-processing (resampling, orientation normalization, data augmentation, etc.) before exporting the database.