CT image pulmonary nodule detection system based on 3D full-connection convolution neural network
A convolutional neural network, CT image technology, applied in biological neural network model, image enhancement, image analysis and other directions, can solve the problems of difficult training, too small lung nodule target, unbalanced samples, etc., to eliminate false detection. Effect
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[0022] The inventive concept of the present invention is: adopt full convolutional segmentation network to perform pixel-level detection and positioning, and use convolutional classification network to suppress false positive targets. The present invention will be further described below in conjunction with the accompanying drawings and implementation examples. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the invention can be carried out in many other ways than those described herein and thus the invention is not limited to the specific implementations disclosed below. figure 1 It is a flow chart of the CT image pulmonary nodule detection system based on the 3D fully connected convolutional neural network of the present invention.
[0023] Including: step S01 training data set construction. Including: data preprocessing, training area selection, data enhancement, etc. T...
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