Overview

ImFusion Labels provides a user-friendly way of:

• managing a database of images coming from multiple sources

• annotating or segmenting images, volumes or even sequences in a few clicks

• exporting all annotations in a standardized way (for instance to train a machine learning model)

The key advantages of ImFusion Labels over other solutions include:

• its genericity since it is not restricted to a particular modality of clinical applications

• the support of a large variety of data formats, including DICOM images

• a toolset of segmentation algorithms that have been designed to be fast and powerful

• Python integration, enabling users to write their own algorithms to label data

• powerful and customizable visualization of data and their annotation

• the possibility to easily define post-processing (resampling, orientation normalization, data augmentation, etc.) before exporting the database

• the access to the ImFusion Suite algorithms within the ImFusion Python module