Analysis of various image processing approaches in detecting and predicting lung cancer

Abstract

Image processing is one of the centre area that utilised in different domains. It is utilised to categorise cancer influenced areas in lung image. Early discovery of lung cancer can build the opportunity of endurance among people. Recognisable proof of cancer influenced areas in lung is basically started with image processing techniques. The techniques are followed by pre-processing having image enhancement along with noise removal using filtering techniques then Image segmentation with feature extraction. Finally, Classification of lung cancer and performance comparison of chronological data of lung cancer. Typically, Digital Image Processing follows numerous strategies to join various shapes in an image into a solitary unit. Despite the fact that Computed Tomography (CT) can be more proficient than X-ray. For detecting and predicting lung cancer, digital image processing techniques can be very much useful for radiologists. In this study, here MATLAB software is used and we discussed about an efficient study on performance analysis techniques in lung cancer detection and prediction by using different image processing methodologies.