Analysis of LIDC-IDRI Pulmonary Nodules Data and Its Significance for Building a Shared Dataset of Traditional Chinese Medicine
This article analyzes the LIDC-IDRI dataset,and trains annotated medical images using convolutional neural networks,long-term and short-term memory networks,and tests them using relevant test datasets.For the corresponding test data,relevant algorithms can be used for initial screening to handle repetitive and cumbersome preliminary judgment tasks.Due to the judgment of traditional Chinese medicine syndrome types,it is similar to the detection of pulmonary nodules,but more complex.Therefore,the deep learning neural network framework has specific reference significance for the discrimination of traditional Chinese medicine syndrome types,and is also a way to integrate traditional Chinese and Western medicine.
LIDC-IDRIpulmonary nodulesDICOMtraditional Chinese medicine shared datasetrecurrent neural networkconvolutional neural network
万方数据
维普
