Convolutional neural network automatic segmentation method and system for mammary molybdenum target data set

The invention discloses a convolutional neural network automatic segmentation method and system for a mammary molybdenum target data set, which can obviously reduce model parameters and improve the practicability while ensuring the precision of a deep learning model on a mammary molybdenum target small data set. The method comprises the following steps: pre-training a convolutional neural big network on a mammary molybdenum target big data set; performing model compression on the trained convolutional neural large network by adopting attention transfer and knowledge distillation methods to obtain a convolutional neural small network; and carrying out fine tuning on the convolutional neural small network on the mammary molybdenum target small data set. 本发明公开了一种用于乳腺钼靶数据集的卷积神经网络自动分割方法及系统，在保证深度学习模型在乳腺钼靶小数据集上的精度的同时，明显降低模型参数，提高实用性。该方法包括以下步骤：在乳腺钼靶大数据集上对卷积神经大网络进行预训练；采用注意力转移和知识蒸馏方法对训练好的卷积神经大网络进行模型压缩，得到卷积神经小网络；在乳腺钼靶小数据集上对卷积神经小网络进行微调。