基于Unet 对肝肿瘤分割（LITS）切片的分割项目【包含数据集、完整代码、训练的结果文件】

[train hyper-parameters: Namespace(base_size=500, batch_size=8, crop_size=480, epochs=10, lr=0.01, lrf=0.001)] [epoch: 1] global correct: 0.9555 precision: ['0.9846', '0.7384', '0.0000'] recall: ['0.9705', '0.8759', '0.0000'] IoU: ['0.9560', '0.6685', '0.0000'] mean IoU: 0.5415 [epoch: 2] global correct: 0.9525 precision: ['0.9934', '0.6927', '0.0000'] recall: ['0.9592', '0.9473', '0.0000'] IoU: ['0.9531', '0.6670', '0.0000'] mean IoU: 0.5400 [epoch: 3] global correct: 0.9715 precision: ['0.9885', '0.8323', '0.0000'] recall: ['0.9842', '0.9137', '0.0000'] IoU: ['0.9730', '0.7716', '0.0000'] mean IoU: 0.5816 [epoch: 4] global correct: 0.9769 precision: ['0.9941', '0.8420', '0.0000'] recall: ['0.9858', '0.9541', '0.0000'] IoU: ['0.9800', '0.8092', '0.0000'] mean IoU: 0.5964 [epoch: 5] global correct: 0.9822 precision: ['0.9926', '0.9008', '0.7736'] recall: ['0.9903', '0.9355', '0.5310'] IoU: ['0.9831', '0.8481', '0.4596'] mean IoU: 0.7636 [epoch: 6] global correct: 0.9800 precision: ['0.9951', '0.8662', '0.7146'] recall: ['0.9860', '0.9567', '0.4484'] IoU: ['0.9812', '0.8335', '0.3803'] mean IoU: 0.7317 [epoch: 7] global correct: 0.9836 precision: ['0.9888', '0.9389', '0.8609'] recall: ['0.9956', '0.9078', '0.4291'] IoU: ['0.9845', '0.8572', '0.4013'] mean IoU: 0.7477 [epoch: 8] global correct: 0.9864 precision: ['0.9949', '0.9236', '0.7633'] recall: ['0.9922', '0.9499', '0.7055'] IoU: ['0.9872', '0.8807', '0.5789'] mean IoU: 0.8156 [epoch: 9] global correct: 0.9881 precision: ['0.9946', '0.9377', '0.8382'] recall: ['0.9942', '0.9498', '0.7000'] IoU: ['0.9889', '0.8934', '0.6167'] mean IoU: 0.8330 [epoch: 10] global correct: 0.9886 precision: ['0.9950', '0.9392', '0.8320'] recall: ['0.9942', '0.9535', '0.7187'] IoU: ['0.9893', '0.8981', '0.6276'] mean IoU: 0.8383