Recognition of Lung Cancer Using CNN Model

Recognition of Lung Cancer Using CNN Model

1 Ms. Sukhwani Divya M., 2 Dr. Pawar U. B., 3 Prof. Daund R. P.

1 PG Student, 2 Asso. Professor, 3Asst. Professor,

1Department of Computer Engineering,

1SNDCOERC, Yeola, India

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Abstract:  Lung cancer is one of the deadliest types of cancer; thousands of people are infected with this type of cancer, and if it is not detected in the early stages of the disease, then the patient's chance of survival will be very small. For the above reasons and to help overcome this terrible early diagnosis with the help of artificial intelligence procedures are most needed. It is also one of the most common and contributing to death among all cancers. Cases of lung cancer are increasing rapidly. There are about 70,000 cases a year in India. In the past decade, cancer detection using deep learning models has been a hot topic, especially in medical image classification. It is worth noting that CNN models are more advanced in dealing with the diagnosis of diseases such as lung cancer due to the higher performance and capabilities of CNNs. This system presents an approach that uses a convolutional neural network (CNN) to classify tumors located in the lungs as malignant or benign. The accuracy obtained by CNN is 99%, which is more efficient compared to the accuracy achieved by traditional existing systems. This is done by applying a convolutional neural network technique to a dataset of lung cancer CT scans.

Index Terms - lung, computed tomography, convolutional neural network, detection, classification