Research on Lung Nodule Detection Based on Improved Target Detection Network

Joint Authors

Li, Ye
Wu, Qian
Sun, Hongwei
Wang, Xuewei

Source

Complexity

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-17

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Philosophy

Abstract EN

Lung nodules are an early symptom of lung cancer.

The earlier they are found, the more beneficial it is for treatment.

However, in practice, Chinese doctors are likely to cause misdiagnosis.

Therefore, deep learning is introduced, an improved target detection network is used, and public datasets are used to diagnose and identify lung nodules.

This paper selects the Mask-RCNN network and uses the dense block structure of Densenet and the channel shuffle convolution method to improve the Mask-RCNN network.

The experimental results prove that proposed algorithm is extremely effective.

American Psychological Association (APA)

Li, Ye& Wu, Qian& Sun, Hongwei& Wang, Xuewei. 2020. Research on Lung Nodule Detection Based on Improved Target Detection Network. Complexity،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1143087

Modern Language Association (MLA)

Li, Ye…[et al.]. Research on Lung Nodule Detection Based on Improved Target Detection Network. Complexity No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1143087

American Medical Association (AMA)

Li, Ye& Wu, Qian& Sun, Hongwei& Wang, Xuewei. Research on Lung Nodule Detection Based on Improved Target Detection Network. Complexity. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1143087

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1143087