Abstract
Lung cancer is the main basis of cancer death amongst men and women, making up almost 25% of the world’s total cancer deaths. Lung cancer described for nearly 1.6 million deaths in 2012 and 1.80 million deaths in 2020. Small cell lung cancer and non-small-cell lung cancer are the two key categories of Lung cancer. The signs of lung cancer include hemoptysis, weight loss, shortness of breath and chest pain. Lung cancer treated by chemotherapy, surgery and CT scan. In this review paper, one of the most crucial zones aiming lung cancer diagnosis has been discussed. Computer-aided diagnosis (CAD) systems adapted for lung cancer can increase the patients’ survival chances. A typical CAD system for lung cancer functions in the fields of lung segmentation, detecting lung nodules and the diagnosis of the nodules as benign or malignant. CAD systems for lung cancer are examined in a huge number of research case studies. CAD system steps and outlining of inhibitor genes at molecular level is being discussed. An insight into multi-omics and molecular dynamics simulations is also given in this paper.
Highlights
Lung cancer can benign and malignant lung tumor caused due to uncontrolled cell growth in the lung tissues. [1,2] The major countries like North America, Europe, and East Asia, along with over one-third of new cases in China are reported of highest number of patients subjected to lung cancer
CT Segmentation techniques: Technical approaches for volumetric lung nodule segmentation suggests that it is classified into 11 categories which are listed below: (i) Thresholding (TH): It yields a binary segmentation of the volume of interest by labelling each voxel by testing whether its intensity value surpasses a specific threshold value or not [49]. (ii) Mathematical Morphology (MM): It is a technique in lung nodule segmentation used for handling cases attached to nontarget structures such as vessels and the parenchymal wall or the diaphragm
Nodule types: CT scan values of parenchymal tissues vary in nature from soft tissues; the segmentation of large solid nodules is not a complex process, whereas small nodules segmentation-based study, where nodules are attached to the vessels, nodules attached to parenchymal wall and diaphragm
Summary
Lung cancer can benign and malignant lung tumor caused due to uncontrolled cell growth in the lung tissues. [1,2] The major countries like North America, Europe, and East Asia, along with over one-third of new cases in China are reported of highest number of patients subjected to lung cancer. Lung cancer can benign and malignant lung tumor caused due to uncontrolled cell growth in the lung tissues. The two main subcategories of lung cancer are small-cell lung carcinoma (SCLC) and non-small-cell lung carcinoma (NSCLC) [8]. Are broadly categorized into three sub-categories, adenocarcinoma, squamous cell carcinoma, and large cell carcinoma These three categories of lung carcinoma are broadly subjected to research studies. In the various research studies conducted in USA, the foremost lifetime risk of lung cancer development is 0.8% in men and 0.6% in women are reported so far [15]. Pathogenesis of lung cancer involves activating oncogenes or inactivation of tumor suppressor genes in the lungs [17]. Thorough process in developing CAD systems, lung segmentation, nodule detection, nodule segmentation, and nodule diagnosis are addressed
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