Lung Cancer Detection using Deep Learning

Lung Cancer Detection using Deep Learning

Prof. Prerana Kulkarni1, Mrunal Sontakke2, Isha Jaiswal3, Soham Bhujbal4, Hitesh Poonia5

1-5Department of Computer Engineering & Pillai College of Engineering(Autonomous), New Panvel, India

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Abstract -  Higher resolution images created by modern 3D medical imaging techniques have the potential to lead to significant advancements in research and medicine. There is a need to create one of the most significant disciplines of scientific imaging because of improvements in computer-aided diagnosis and ongoing developments in the area of computerized medical image visualization. Lung cancer is one of the most prevalent malignancies among the many different types of cancer. Lung cancer detection commonly makes use of computed tomography (CT) images. Techniques for machine learning are frequently employed for lung cancer detection.CNN is a technique for describing deep learning models that have filters that may be learned through local pooling operations that are alternately implemented on input CT images to produce a variety of hierarchical or complex features. The method used in this project classifies lung cancer or normal tissue seen during computed tomography images for screening as Lung Cancer or Normal using a convolutional neural network (CNN).

Key Words:  Lung Cancer Detection, Deep Learning, Image processing, Feature extraction, Convolutional Neural Network (CNN), CT Images.