Early Detection of Lung Cancer with Low-Dose CT Scan Using Artificial Intelligence: A Comprehensive Survey

被引:0
|
作者
Thakral G. [1 ]
Gambhir S. [1 ]
机构
[1] Department of Computer Engineering, J. C. Bose University of Science and Technology, YMCA, Faridabad
关键词
Deep neural network; Early detection; Low-dose CT scan; Lung nodules; Machine learning;
D O I
10.1007/s42979-024-02811-7
中图分类号
学科分类号
摘要
Lung cancer is generally caused by an abnormal expansion of cells in the lungs of people due to mutation. In the lungs, the smallest unit of cell growth is named lung nodules that vary from 5 to 25 mm in diameter. Finding lung nodules at an early time is crucial. Researchers have used numerous methods to detect lung nodules at earlier stage. These methods have their own advantages and restrictions. The extensive literature review concludes that Low Dose CT scan is one of the most successful way for early-stage pulmonary nodule detection. In this work, a critical analysis of different strategies for early identification of lung nodules has been discussed along with its current trends, performance metrics, and future challenges. This paper also included details of available data-sets. The aim of this study is to evaluate different approaches for employing LDCT images to identify lung cancer at initial level. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.
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