linkenfaqiu / MMRAN

这是《Multitask Learning with Multiscale Residual Attention for Brain Tumor Segmentation and Classification》这篇文章的源代码。若要使用,请对data文件夹进行数据划分后,输入$python main.py train$
https://link.springer.com/article/10.1007/s11633-022-1392-6
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beginner-friendly brain-tumor-classification brain-tumor-segmentation multi-task-learning

MMRAN

这是《Multitask Learning with Multiscale Residual Attention for Brain Tumor Segmentation and Classification》这篇文章的源代码,收录自《Machine Intelligence Research》。

请先将data文件夹按照您需要的比例对数据进行划分,之后输入$python main.py train$进行模型训练,输入$python main.py test$进行模型测试。

数据集来源:https://figshare.com/articles/dataset/brain_tumor_dataset/1512427

关于数据集的一些细节可以参考文章的4.1节:https://link.springer.com/article/10.1007/s11633-022-1392-6


This is the source code for the article "Multitask Learning with Multiscale Residual Attention for Brain Tumor Segmentation and Classification", included in Machine Intelligence Research.

First, divide the data folder into training set, validation set, and test set in the scale you need. After that, enter "python main.py train" for model training and "python main.py test" for model testing.

Data set source: https://figshare.com/articles/dataset/brain_tumor_dataset/1512427

For some details about the dataset, please refer to section 4.1 of the article: https://link.springer.com/article/10.1007/s11633-022-1392-6