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BraTS Toolkit: Translating BraTS Brain Tumor Segmentation Algorithms Into Clinical and Scientific Practice
Florian Kofler1,2, Christoph Berger1, Diana Waldmannstetter1
1Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany.
Frontiers in Neuroscience
|May 16, 2020
Summary
This study introduces BraTS Toolkit, a comprehensive solution for brain tumor segmentation. It addresses challenges in data standardization and preprocessing, enabling easier clinical translation of advanced algorithms.
Area of Science:
- Medical image analysis
- Computational neuroimaging
- Oncology
Background:
- Translating advanced computational methods for brain tumor segmentation into clinical practice is hindered by data standardization and preprocessing challenges.
- Effective image analysis requires robust preprocessing steps for accurate segmentation algorithms.
Purpose of the Study:
- To present BraTS Toolkit, a holistic solution designed to streamline brain tumor segmentation.
- To facilitate the translation of state-of-the-art segmentation algorithms into clinical and scientific practice.
Main Methods:
- BraTS Toolkit comprises three components: BraTS Preprocessor for data standardization and preprocessing (conversion, registration, brain extraction), BraTS Segmentor for automated segmentation, and Brats Fusionator for consensus segmentation using fusion methods.
- The toolkit supports the entire image analysis workflow prior to segmentation.
Main Results:
- The BraTS Toolkit provides a standardized and automated approach to brain tumor segmentation.
- Demonstrated through a practical example, the toolkit simplifies the implementation of advanced segmentation techniques.
Conclusions:
- BraTS Toolkit offers a comprehensive solution to overcome challenges in brain tumor segmentation, improving the accessibility and applicability of computational methods.
- The toolkit facilitates the seamless integration of advanced brain tumor segmentation techniques into research and clinical settings.
