March 14, 2024, 4:46 a.m. | Linjie Fu, Xia Li, Xiuding Cai, Yingkai Wang, Xueyao Wang, Yali Shen, Yu Yao

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.08479v1 Announce Type: cross
Abstract: Radiation therapy is crucial in cancer treatment. Experienced experts typically iteratively generate high-quality dose distribution maps, forming the basis for excellent radiation therapy plans. Therefore, automated prediction of dose distribution maps is significant in expediting the treatment process and providing a better starting point for developing radiation therapy plans. With the remarkable results of diffusion models in predicting high-frequency regions of dose distribution maps, dose prediction methods based on diffusion models have been extensively studied. …

abstract arxiv automated cancer cancer treatment cs.cv diffusion diffusion model distribution eess.iv experts generate mamba maps physics.med-ph prediction process quality therapy treatment type

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