Lung Nodule Detection and Classification using Image Processing Techniques
Ms. Swathi Velugoti, Ms. Revuri Harshini Reddy, Ms. Sadiya Tarannum , Mr. Sama Tharun Kumar Reddy,
Affiliations Department of Computer Science and Engineering, Guru Nanak Institutions Technical Campus Hyderabad – Telangana, India
Lung cancer is one of the significant reasons for death among India. Many diagnosis and detection of lungs cancer has been done using various data analysis and classification techniques. Since the cause of lung cancer stay obscure, prevention become impossible, thus early detection of tumor in lungs is the only way to cure lung cancer. Hence, lung cancer detection system using image processing and machine learning is used to classify the presence of lung cancer in a CT- images and blood samples. In spite of CT scan reports are more effective than Mammography; therefore patient CT scan images are categorized in normal and abnormal. The abnormal images are subjected to segmentation to focus on tumor portion. Classification done on features extracted from the images. The efficient method to detect the lung cancer and its stages successfully and also aim to have more accurate results by using SVM and Image Processing techniques.
Ms. Swathi Velugoti ,Ms. Revuri Harshini Reddy,Ms. Sadiya Tarannum,Mr. Sama Tharun Kumar Reddy."Lung Nodule Detection and Classification using Image Processing Techniques". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.9, Issue 07,pp.114-119, July - 2022, URL :https://ijcert.org/ems/ijcert_papers/V9I701.pdf,
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