Lung Cancer Detection and Prediction Using Customized Selective Segmentation Technique with SVM Classifier

2021 ◽  
pp. 37-44
Author(s):  
S. S. Ashwini ◽  
M. Z. Kurian ◽  
M. Nagaraja
Keyword(s):  
Lung Cancer ◽  
Cancer Detection ◽  
Svm Classifier ◽  
Segmentation Technique ◽  
Lung Cancer Detection

A Comparative Study of Image Segmentation Technique applied for Lung Cancer Detection

2019 ◽  
Author(s):  
Mohd Firdaus Abdullah ◽  
Muhammad Safwan Mansor ◽  
Siti Noraini Sulaiman ◽  
Muhammad Khusairi Osman ◽  
Nur Najihah Sofea Mohd Marzuki ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Image Segmentation ◽  
Comparative Study ◽  
Cancer Detection ◽  
Segmentation Technique ◽  
Lung Cancer Detection

scholarly journals CDCT: CT Scan Images based on Mechanism for Lung Cancer Detection

2019 ◽  
Vol 8 (2S6) ◽  
pp. 931-935
Keyword(s):  
Lung Cancer ◽  
Ct Scan ◽  
Cancer Detection ◽  
Support Vector ◽  
Svm Classifier ◽  
Comparison Analysis ◽  
Early Analysis ◽  
Proficiency Level ◽  
Traditional Work ◽  
Lung Cancer Detection

Image classification is one of the major issues of image pre-processing approach. To resolve this issue a large number of classification approaches has been developed. In this work, a novel SVM-FA (support vector machine optimized with firefly approach) classifier is developed for detecting the lung cancer on the basis of the CT images. Lung cancer is considered one of the most critical and vital. Thus the early analysis of such kind of disease is required. For this purpose, the study implements the image pre-processing (filtration and segmentation) techniques to the input CT scan images. Then the SVM classifier, optimized with firefly approach is applied to the pre-processed data. The target of the work is to enhance the accuracy in the final prediction or output. For evaluating the proficiency level of the proposed SVM-FA approach, a comparison analysis is also performed in this work. The comparison is done among proposed work, traditional work and SVM classifier. On the basis of the obtained facts and figures, the proposed work is found to be effective and efficient in terms of the accuracy (96%) and specificity (83.333%) respectively

Green synthesis of nanomaterials for early lung cancer detection

2018 ◽  
pp. 1-1
Keyword(s):  
Lung Cancer ◽  
Green Synthesis ◽  
Cancer Detection ◽  
World Wide ◽  
Early Stage ◽  
Age Groups ◽  
Early Lung Cancer ◽  
Lung Cancer Detection ◽  
Synthesis Of Nanomaterials

Lung cancer is the foremost cause of cancer-related deaths world-wide [1]. It affects 100,000 Americans of the smoking population every year of all age groups, particularly those above 50 years of the smoking population [2]. In India, 51,000 lung cancer deaths were reported in 2012, which include 41,000 men and 10,000 women [3]. It is the leading cause of cancer deaths in men; however, in women, it ranked ninth among all cancerous deaths [4]. It is possible to detect the lung cancer at a very early stage, providing a much higher chance of survival for the patients.

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