BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis
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arXiv
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| Autori principali: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| author | Kofler, Florian Rosier, Marcel Astaraki, Mehdi Möller, Hendrik Mekki, Ilhem Isra Buchner, Josef A. Schmick, Anton Pfiffer, Arianna Oswald, Eva Zimmer, Lucas de la Rosa, Ezequiel Pati, Sarthak Canisius, Julian Piffer, Arianna Baid, Ujjwal Valizadeh, Mahyar Linardos, Akis Peeken, Jan C. Shit, Surprosanna Steinbauer, Felix Rueckert, Daniel Heckemann, Rolf Bakas, Spyridon Kirschke, Jan von See, Constantin Ezhov, Ivan Piraud, Marie Wiestler, Benedikt Menze, Bjoern |
| author_facet | Kofler, Florian Rosier, Marcel Astaraki, Mehdi Möller, Hendrik Mekki, Ilhem Isra Buchner, Josef A. Schmick, Anton Pfiffer, Arianna Oswald, Eva Zimmer, Lucas de la Rosa, Ezequiel Pati, Sarthak Canisius, Julian Piffer, Arianna Baid, Ujjwal Valizadeh, Mahyar Linardos, Akis Peeken, Jan C. Shit, Surprosanna Steinbauer, Felix Rueckert, Daniel Heckemann, Rolf Bakas, Spyridon Kirschke, Jan von See, Constantin Ezhov, Ivan Piraud, Marie Wiestler, Benedikt Menze, Bjoern |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_09036 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis Kofler, Florian Rosier, Marcel Astaraki, Mehdi Möller, Hendrik Mekki, Ilhem Isra Buchner, Josef A. Schmick, Anton Pfiffer, Arianna Oswald, Eva Zimmer, Lucas de la Rosa, Ezequiel Pati, Sarthak Canisius, Julian Piffer, Arianna Baid, Ujjwal Valizadeh, Mahyar Linardos, Akis Peeken, Jan C. Shit, Surprosanna Steinbauer, Felix Rueckert, Daniel Heckemann, Rolf Bakas, Spyridon Kirschke, Jan von See, Constantin Ezhov, Ivan Piraud, Marie Wiestler, Benedikt Menze, Bjoern Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Software Engineering 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. |
| title | BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Software Engineering |
| url | https://arxiv.org/abs/2507.09036 |