Advancing Brain Tumor Inpainting with Generative Models
<|reference_start|>Advancing Brain Tumor Inpainting with Generative Models: Synthesizing healthy brain scans from diseased brain scans offers a potential solution to address the limitations of general-purpose algorithms, such as tissue segmentation and brain extraction algorithms, which may not effectively handle diseased images. We consider this a 3D inpainting task and investigate the adaptation of 2D inpainting methods to meet the requirements of 3D magnetic resonance imaging(MRI) data. Our contributions encompass potential modifications tailored to MRI-specific needs, and we conducted evaluations of multiple inpainting techniques using the BraTS2023 Inpainting datasets to assess their efficacy and limitations.<|reference_end|>
@article{zhu2024advancing,
    title={Advancing Brain Tumor Inpainting with Generative Models},
    author={Ruizhi Zhu, Xinru Zhang, Haowen Pang, Chundan Xu, Chuyang Ye},
    journal={arXiv preprint arXiv:2402.01509},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.01509},
    primaryClass={eess.IV cs.CV cs.LG}
}