(EN) The embodiment of the invention provides an automatic nasopharyngeal carcinoma primary tumor image identification method and system. Multi-modal input of a semantic segmentation network model is formed based on a CT three-dimensional image of a tested person and an MR sequence three-dimensional image, and identification of a nasopharyngeal carcinoma primary tumor on CT is realized. By combining the CT three-dimensional image and the MR sequence three-dimensional image, the quality of input data can be effectively improved, global information and detail information of a high-resolution image can be learned, the prediction accuracy and generalization ability of the semantic segmentation network model can be effectively improved, the flexibility of an input end and an output end is achieved,and the working efficiency of medical workers is effectively improved.
(ZH) 本发明实施例提供了一种鼻咽癌原发肿瘤图像自动识别方法及系统，以被测者的CT三维图像为基础，辅以MR序列三维图像，构成了语义分割网络模型的一个多模态输入，实现在CT上的鼻咽癌原发肿瘤识别。结合CT三维图像与MR序列三维图像，能有效提高输入数据的质量，并学习到高分辨率图像的全局信息和细节信息，能有效提高语义分割网络模型的预测准确度和泛化能力，并具备输入端与输出端的灵活性，进而有效提高医疗工作者的工作效率。
