Graph-based brain tumor segmentation using superpixels and GNNs
Project description
GlioGraphSeg
GlioGraphSeg is a deep learning-based tool for brain tumor segmentation from MRI scans. It uses Graph Neural Networks to model spatial relationships between regions. The system provides accurate glioma detection and segmentation.
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Description
GlioGraphSeg combines deep learning and graph-based modeling to improve the segmentation of gliomas in brain MRI scans.
The tool is designed to support medical professionals by providing accurate, automated tumor delineation using GNNs.
Citation
If you use GlioGraphSeg in your research, please cite the following paper:
Amato, D., Calderaro, S., Bosco, G. L., Rizzo, R., & Vella, F. (2024, December). Semantic Segmentation of Gliomas on Brain MRIs by Graph Convolutional Neural Networks. In 2024 International Conference on AI x Data and Knowledge Engineering (AIxDKE) (pp. 143-149). IEEE. DOI link
Contact
For questions or collaborations, contact: salvatore.calderaro01@unipa.it
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