Abstract:

The largest cause of cancer-related fatalities worldwide is lung cancer. One type of cancer that starts in the lungs is lung cancer. Your lungs are two pliable organs located in your chest that allow you to breathe in oxygen and exhaust carbon dioxide. Medical imaging technologies are required for both the early detection of lung cancer and the ongoing monitoring of lung cancer throughout treatment. Chest X-rays, magnetic resonance imaging, positron emission tomography, computed tomography, and molecular imaging techniques have all been extensively studied for the detection of lung cancer.These methods have some drawbacks, such as the inability to automatically categorise cancer photos, which makes them unsuitable for patients with other illnesses. The creation of a sensitive and precise method for the early diagnosis of lung cancer is urgently required. With quickly developing applications across, deep learning is one of the medical imaging fields that is expanding the fastest. The detection and classification of lung nodules can be done more rapidly and accurately by physicians

Description:

Computed Tomography images, Segmentation, Deep learning, Lung cancer, Convolution neural networks, Classification