An exhaustive analysis of Feature extraction techniques for identifying diseased lungs from CT Images

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Dr. M. MUTHURAMAN

Abstract

LDs (Lung Diseases) when considered cumulatively, are a major cause of morbidity and mortality. Many times, CTSIs (Computed Tomography Scan Images) are obtained by doctors for evaluation of LDs and condition of patients including pneumonia, COVID-19, cancer, blood clots or other damages caused in the lungs. CTSIs of internal organs, bones, soft tissue, and blood vessels detail about these parts to clinicians and specifically their details on soft tissues and blood vessels are of great use. Hence, assessments of LDs can be done using CTSIs. These images can also be processed using IPTs (Image Processing Techniques) which are non-invasive ways of examinations. The most important part of IPTs in CTSIs are FEs (Feature Extractions) which are central to diagnosis or classifications or detections of LDs. FEs in the case of LDs from CTSIs narrows down to identification of diseased areas precisely where multitude of techniques are used. This paper presents a thorough analysis of the existing techniques for FEs with comparative performance charts.

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