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Accurate detection and segmentation of brain tumors is critical for medical diagnosis. We propose a novel framework Two-Stage Generative Model (TSGM) that combines Cycle Generative Adversarial Network (CycleGAN) and Variance Exploding stochastic differential equation using joint probability (VE-JP) to improve brain tumor segmentation. TSGM was trained on the BraTs2020 brain tumor dataset.
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it contains the low-dose CT images used in the experiment.
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This is an accurately labeled dataset designed to support foreign bodies detection research in industrial production scenarios. In order to facilitate the reproduction of the results of the original paper, we provide this dataset for further research.
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