Abstract
Cellular breakdown in the lungs tends to be a frequent cause of death in people all over the world. Individuals who are diagnosed with lung disease early on have a greater chance of survival. If the condition is diagnosed as predicted, the average 5-year survival rate for lung cancer patients rises from 14 to 49%. Despite the fact that computed Tomography (CT) is often more effective than X-ray. However, the problem tended to merge due to the time constraints in identifying the existence of malignant growth in the lungs, as well as the limited diagnostic techniques available. As a result, in CT pictures, a lung cancer identification system based on picture preparation is used to group the presence of cellular breakdown in the lungs. Using various update and division methods, the aim is to obtain more reliable results.
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Singh, B.D., Sharma, C., Khanna, A. (2022). Lung Cancer Detection in Radiographs Using Image Processing Techniques. In: Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1388. Springer, Singapore. https://doi.org/10.1007/978-981-16-2597-8_41
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DOI: https://doi.org/10.1007/978-981-16-2597-8_41
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