Noise removal methodologies for lung cancer diagnosis - Nur Fatin Razlieya, Mohd Razali (2019)
Noise reduction is the one of the step in image processing where the process of reducing noise from an image. The noise present in the images such as in a medical image like Salt and Paper Noise, Gaussian Noise and others. Different noises have their own characteristics which make them identifiable from others. However, enhanced the image especially the medical images is required by doctors to help the diagnosis and interpretation because lack of images quality due to the noise. The methods of noise removal was be analysed from existing paper in literature review. Based on the existing paper, each of the method had their own benefits and drawbacks. Therefore, the uses of suitable method is important to improve the quality of medical image for early diagnosis of lung cancer. In this paper, Gaussian Filter and Median Filter is proposed for removing the noise from CT scan images. The objective of the study is to implement and develop the method of noise removal for lung cancer diagnosis. The development research methodology presented five fundamental stage which are investigation of existing method of noise removal, developing a new method for noise removal, implementation of the noise removal method, verification and validation. Therefore, the algorithm will be developed and implemented in MATLAB software. Then, the method will be tested and verified to detect the cancer in the lung image. The result of CT scan image of lung cancer were showed and to validated the performance of this proposed method.