BrainLesion Suite is a versatile toolkit for building modular brain lesion image analysis pipelines in Python. Following Pythonic principles, BrainLesion Suite is designed to provide a 'brainless' development experience, minimizing cognitive effort and streamlining the creation of complex workflows for clinical and scientific practice. At its core is an adaptable preprocessing module that performs co-registration, atlas registration, and optional skull-stripping and defacing on arbitrary multi-modal input images. BrainLesion Suite leverages algorithms from the BraTS challenge to synthesize missing modalities, inpaint lesions, and generate pathology-specific tumor segmentations. BrainLesion Suite also enables quantifying segmentation model performance, with tools such as panoptica to compute lesion-wise metrics. Although BrainLesion Suite was originally developed for image analysis pipelines of brain lesions such as glioma, metastasis, and multiple sclerosis, it can be adapted for other biomedical image analysis applications. The individual BrainLesion Suite packages and tutorials are accessible on GitHub.
@article{arxiv.2507.09036,
title = {BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis},
author = {Florian Kofler and Marcel Rosier and Mehdi Astaraki and Hendrik Möller and Ilhem Isra Mekki and Josef A. Buchner and Anton Schmick and Arianna Pfiffer and Eva Oswald and Lucas Zimmer and Ezequiel de la Rosa and Sarthak Pati and Julian Canisius and Arianna Piffer and Ujjwal Baid and Mahyar Valizadeh and Akis Linardos and Jan C. Peeken and Surprosanna Shit and Felix Steinbauer and Daniel Rueckert and Rolf Heckemann and Spyridon Bakas and Jan Kirschke and Constantin von See and Ivan Ezhov and Marie Piraud and Benedikt Wiestler and Bjoern Menze},
journal= {arXiv preprint arXiv:2507.09036},
year = {2025}
}