Advancing Brain Tumor Inpainting with Generative Models

Ruizhi Zhu, Xinru Zhang, Haowen Pang, Chundan Xu, Chuyang Ye
2/2/2024
eess.IVcs.CVcs.LG

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Abstract

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.

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Cite this paper

@article{zhu2024advancing,
  title  = {Advancing Brain Tumor Inpainting with Generative Models},
  author = {Ruizhi Zhu and Xinru Zhang and Haowen Pang and Chundan Xu and Chuyang Ye},
  year   = {2024},
  eprint = {2402.01509},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.01509v1}
}

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