A Survey of Noise Removal Methodologies for Lung Cancer Diagnosis

Abstract

Investigation of signal and image are presently an essential step of the heart diseases processes like diagnostic, prognostic and follow-up. Lung cancer is the most intense type of cancer among every type of cancer with less rate of survival. It is exceptionally hard to examine the cancer at its initial stage. In the previous couple of years, numerous Computer aided systems have been intended to distinguish the lung cancer at its initial stage. In medical imaging, diverse types of images are being utilized yet for the detection of diagnosis of lungs. In medical imaging, detection of nodule is standout amongst the challenging tasks. Computed Tomography (CT) images are generally preferred due to less distortion, low noise and better clarity. Detecting and then curing that disease in the initial stages offers the patients with higher possibility of survival. There are different types of the noise present in the images we obtain for the lung mass detection like salt and pepper noise, Gaussian noise and speckle noise. This paper is based on quality improvement analysis of digital dental X-ray image. Removal of noise from images is the most active field of research. This paper presents the review on the lung cancer, types of noise in medical imaging and then the methods for the removal of noise.