Advancing Brain Tumor Inpainting with Generative Models
- URL: http://arxiv.org/abs/2402.01509v1
- Date: Fri, 2 Feb 2024 15:43:51 GMT
- Title: Advancing Brain Tumor Inpainting with Generative Models
- Authors: Ruizhi Zhu, Xinru Zhang, Haowen Pang, Chundan Xu, Chuyang Ye
- Abstract summary: Synthesizing healthy brain scans from diseased brain scans offers a potential solution to address the limitations of general-purpose algorithms.
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.
- Score: 0.7499722271664147
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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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