Transfer learning is commonly used in deep learning for medical imaging to alleviate the problem of limited available data. In this work, we studied the risk of feature leakage and its dependence on sample size when using pretrained deep convolutional neural network (DCNN) as feature extractor for classification breast masses in mammography.

中文翻译：

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乳腺肿块分类深度特征提取中的特征泄漏和样本大小依赖性风险


迁移学习通常用于医学成像的深度学习中，以缓解可用数据有限的问题。在这项工作中，我们研究了使用预训练的深度卷积神经网络（DCNN）作为乳腺 X 线摄影中乳腺肿块分类的特征提取器时的特征泄漏风险及其对样本大小的依赖性。