Categorizing the stages of lung cancer using Multi SVM Classifier

Abstract

Detection of cancer is the utmost fascinating analysis space for scientists in the early period. The projected method is meant to identify cancer in the beginning phase. The projected method comprises several phases, such as image acquisition, pre-processing, segmentation, feature extraction, and classification. In our proposed work, segmentation is done to fragment the CT image. We use solid feature extraction (GLCM) technique to extract certain essential features from the segmented images. Further extracted features are considered for classification (Multi SVM) process to check whether cancerous or non-cancerous.

Lung Cancer Prediction and Detection Using Image Processing Mechanisms: An Overview

“…Ashwini et al, 2019, [19] in this study an image processing mechanisms had been proposed for identifying and estimating Lung-Cancer cells. A multi support-vector machine had been used as a classifier to differentiate the nodules as either malignant or benign.…”