Digital Image Processing Methods for Detecting Cancer Cells: A Review

In recent years, image processing mechanisms have been widely used in several medical areas to improve early detection and treatment phases, in which the time factor is very important for the patient to discover the disease as quickly as possible, especially in various cancer tumours such as lung cancer. Lung cancer has attracted the attention of the scientific and sciatic communities in recent years due to its high prevalence combined with difficult diagnosis. Statistics show that lung cancer is the one that attacks the largest number of people in the world. Early detection of lung cancer is very critical to successful treatment. There are few methods available to identify cancer cells. Here two segmentation approaches, such as thresholding and watershed, are used to identify cancer cells and to find a better response to them. Cancer diagnosis also requires the application of radiological imaging. Digital image processing is also used to monitor the spread of cancer and the progress of treatment and to monitor cancer. Oncological imagery is becoming increasingly diverse and precise. The aim of digital image processing is to find the most appropriate treatment option for each patient. Imaging methods are often used in conjunction to provide sufficient information.