期刊
出版社
IEEE
DOI: 10.1109/icarm.2019.8834190
关键词
-
资金
- National Natural Science Foundation of China [61571193, 31771016]
- Natural Science Foundation of Guangdong, China [2017A030312006]
Liver cancer has the third highest mortality rate in the world. Effective treatment depends on the accurate identification of benign and malignant tumors. This paper proposed a computer-aided system for distinguishing liver lesions based on CEUS, a widely accepted inspection technique. Video sequences arc handled by the 3D convolutional neural network (3D-CNN) to extract spatial and temporal features. Meanwhile, the framework is trained by a specific dataset to yield a classification network. According to the results, our system obtained higher performance than the previous system. The average accuracy rate reached 93.1% with ten-fold cross-validation. It is noteworthy that the system is potential and easy to expand to other applications.
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