Automated Detection of Lung Cancer Based on Neuro Fuzzy Technique

Abstract

Our human civilization has encountered many dangerous diseases and death due to lung cancer is increasing worldwide. The finding of lung cancer cells in the earliest stage is the most challenging process in the medical field. To address the issue, digital image processing techniques, along with neuro-fuzzy logic, has experimented in this current study. The system is aimed to help in the initial stage detection of lung nodules by classifying the existence of abnormalities in the computed tomography (CT) scan image. The critical stages involved in the detection process are preprocessing, image enhancement, image segmentation, feature extraction and neuro-fuzzy algorithm. The proposed system is an entirely functional automatic method which completely avoids physical calculation and this designed system produces a better result with a high accuracy rate.

Lung Cancer Detection Technique Based on Surf Descriptor and KNN Algorithms

“…Pre-processing, image enhancement, image segmentation, feature extraction, and the neuro-fuzzy algorithm are all important steps in the detection process. The suggested system is a fully automated, fully functional technique that does not need any physical calculations, and it provides a superior outcome with a high accuracy rate has been presented Joshya et al (2021) .…”