Advancing Brain Tumor Inpainting with Generative Models
Ruizhi Zhu Xinru Zhang Haowen Pang Chundan Xu Chuyang Ye
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.