Abstract
The application of image processing techniques for the analysis of CT scan images corresponding to lung cancer cells is gaining momentum in recent years. Therefore, it is of interest to discuss the use of a Computer-Aided Diagnosis (CAD) system using Computed Tomography (CT) images to help in the early diagnosis of lung cancer (to distinguish between benign and malignant tumors). We discuss and explore the design and significance of a CAD-CT image processed model in cancer diagnosis.
Highlights
Small cell lung cancer and non-small cell lung cancer are common types of lung cancer [1]
Images generated by X-rays, Computed-Tomography (CT) scans, Magnetic Resonance Imaging (MRI) and others help in the early detection of lung cancer without surgery
Tomography (CT) images to help in the early diagnosis of lung cancer
Summary
Small cell lung cancer and non-small cell lung cancer are common types of lung cancer [1]. It is of importance to develop new methods for the early detection of lung cancer. An implementation and analysis of the image processing method for the detection of lung cancer is described [7]. Tomography (CT) images to help in the early diagnosis of lung cancer (to differentiate between benign and malignant tumors). Using Computed-Tomography (CT) images to ensure early diagnosis of lung cancer and differentiation between benign and malignant tumors [9] has developed computer-Aided Diagnosis (CAD) system. CAD system: The CAD System has the following features: (1) It improves the diagnosis accuracy; (2) Assist in cancer detection at its earlier stage and (3) Reduces the time of the radiologist in evaluation
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