Lung cancer identification using computerized tomography images

• Published in: AIP conference proceedings Vol. 2850; no. 1
• Main Authors: Jancy, S., Kumar, Sana Prem, Kumar, Rayapati Sai Prasanna, Latha, S. Pushpa, Selvan, Mercy Paul, Mary, A. Viji Amutha, Priyadarshini, E.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 17.05.2024
• Subjects: Algorithms; Computed tomography; Image filters; Lung cancer; Medical imaging; Neural networks; Radiation therapy; Tomography
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0208909

Significant progress has been made in the field of lung cancer over the years (chemical rehabilitation, radiotherapy, individualized treatment). Nevertheless, lung cancer remains a threat to society and a leading cause of death for thousands of people worldwide. The subject of this paper is the diagnosis of lung cancer. Lung cancer is diagnosed using computerized tomography (CT) scans. To accurately diagnose lung cancer, different algorithms are used. The image is filtered through a sharp hidden filter in this case. The edges and areas of the cancer are detected using a flexible canvas method. To identify the features andpredict the risk of lung cancer, using the neural network. The K-Nearest Neighbors method is used to separate cancerand lungs. Lung cancer is diagnosed using computerized tomography (CT) scans. To accurately diagnose lung cancer, different algorithms are used. The image is filtered through a sharp hidden filter in this case. The edges and areas of the cancer are detected using a flexible canvas method. To identify the features and predict the risk of the Using a neural network to study lung cancer. The K-Nearest Neighbors method is used to separate cancer and lungs. Lung cancer has been growing in recent years, so it is very important to know if tumor has turned into cancer. Prognosis occurs early and Accurate predictions can save many lives and assist doctors in starting therapy. CT (computed tomography) is a type of imaging that uses a is important in determining the condition of a plant by determining its size, location, and other factors.