Overview
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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