Detection of early emphysema regions in HRCT images using Fuzzy-C Mean

Chronic obstructive pulmonary disease (COPD) is an irrevocable disorder and has a high mortality rate. It can be diagnosed by using several methods, e.g., traditional radiology imaging, clinical details, and pulmonary function tests (PFTs). Conventional radiology detects the emphysema in its late phases when the disease has already damaged an enormous lung field region. So, high resolution computed tomography (HRCT) is used to precisely estimate the disease's severity. Early emphysema, typically less than 10 mm in diameter, often got missed during a visual assessment of HRCT scans. So an attempt has been made to target this issue. To the best of our knowledge, early emphysema regions' detection using HRCT images was not addressed. This paper proposes a novel method by incorporating details of low attenuation areas (LAA) into Fuzzy-C Mean (FCM) algorithm to identify the uncertain regions of early emphysema regions proficiently in HRCT images. Experimental results are authenticated by using ground truth marked by the expert radiologist. The investigational outcomes show that the proposed method gives results close to expert radiologist's manual demarcations.