Lung Cancer Detection Using CNN
Lung cancer is one of the most lethal cancer types; thousands of peoples are infected with this type of cancer, and if they do not discover it in the early stages of the disease, then the chance of surviving of the patient will be very poor. For the suggested reasons above and to help in overcoming this terrible, early diagnosis with the assistance of artificial intelligence procedures most needed. Also, it is one of the most common and contributing to deaths among all the cancers. Cases of lung cancer are increasing rapidly. There are about 70,000 cases per year in India. Over the past decade, Cancer detection using deep learning models has been a hot topic, especially in medical image classification. It is worth remarking that CNN models are more advanced at addressing diagnose diseases such as lung cancers because of the higher performance and ability of the CNN. This system presents an approach which utilizes a Convolutional Neural Network (CNN) to classify the tumors found in lung as malignant or benign. The accuracy obtained by means of CNN is 99%, which is more efficient when compared to accuracy obtained by the traditional existing systems. This done by applying convolutional neural network technique to a data set of lung cancer CT scans.
PROJECT OUTPUT VIDEO:
ALGORITHM / MODEL USED:
CNN Model Architecture
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- Monitor : 15’’ LED
- Input Devices : Keyboard, Mouse
- Ram : 4 GB
- Operating system : Windows 10.
- Coding Language : Python 3.8
- Web Framework : Flask