Learning Contextual and Attentive Information for Brain Tumor Segmentation
摘要 本文提出了一個單通多任務網絡，組合多個不同的CNNs結構，綜合它們的分割結果來獲取一個更爲精確的最終分割結果。 Dataset :本文采用的數據集是Brats2018 結果 本文在Valiation數據集上取得了79.22、90.74、83.58的dice 數據處理 本文對於數據所進行的處理就是對每張圖像分別進行了圖像歸一化 方法： 將多分類任務分成三個不同但又相關的子任務來處理類別不平衡問
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相關文章
- 1. A deep learning model integrating FCNNs and CRFs for brain tumor segmentation
- 2. 論文筆記：A deep learning model integrating FCNNs and CRFs for brain tumor segmentation
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- 4. Brain tumor segmentation with Deep Neural Networks
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