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The Detection and Recognition of Pulmonary Nodules Based on U-net and CNN

Published: 17 March 2021 Publication History

Abstract

In recent years, with the rapid development of deep learning, especially convolutional neural network technology, deep learning technology has been widely used in various image classification and recognition, including the detection and recognition of pulmonary nodules. However, due to the limitation of computer capability, the input image size of convolutional neural network for deep learning is usually fixed, and the image size is usually small. However, the size of CT images used to detect pulmonary nodules is 512×512 and the sample data for training convolutional neural network is relatively small. It is usually difficult for ordinary convolution neural networks to detect directly. As a special full convolution network, U-net can be used directly for large-scale image detection by replacing the full connection layer with the convolution layer. And U-net is suitable for small sample medical image detection. Therefore, the detection of pulmonary nodules with U-net has been tried in this paper. The detection and recognition of pulmonary nodules is divided into two steps. Firstly, a U-net network is used to detect and segment suspicious pulmonary nodules. Secondly, in order to improve the accuracy of pulmonary nodules detection and recognition, a convolution neural network(CNN) is used to classify and identify the pulmonary nodules segmented by U-net detection, so as to remove the false positive pulmonary nodules. The experimental results show that the pulmonary nodules detection and recognition method combined with U-net and CNN is not only suitable for small sample and large size chest CT image detection, but also can remove a large number of false positive pulmonary nodules, effectively improve the accuracy of pulmonary detection, which is of great significance for the classification and recognition of pulmonary nodules using deep learning technology.

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CSAI '20: Proceedings of the 2020 4th International Conference on Computer Science and Artificial Intelligence
December 2020
294 pages
ISBN:9781450388436
DOI:10.1145/3445815
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 March 2021

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  1. CNN
  2. Deep Learning
  3. Pulmonary Nodules
  4. U-net

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