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

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Abstract

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.

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Authors and Affiliations

  1. Department of Computer Engineering, J. C. Bose University of Science and Technology, YMCA, Faridabad, India

    Gagan Thakral & Sapna Gambhir

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  1. Gagan Thakral
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Contributions

Rigorous Literature study has been done with proposal of potential future directions in early detection of lung cancer with Low-Dose CT scan images using Artificial Intelligence. A comparative analysis of executed research works by many authors in the same field has also been portrayed using tabular form in given review paper.

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Correspondence to Gagan Thakral.

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Thakral, G., Gambhir, S. Early Detection of Lung Cancer with Low-Dose CT Scan Using Artificial Intelligence: A Comprehensive Survey. SN COMPUT. SCI. 5, 441 (2024). https://doi.org/10.1007/s42979-024-02811-7

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