Abstract
Abstract This paper describes a prototype of an automatic system for the detection and evaluation of Cystic fibrosis features (CF) in High resolution computed tomography (HRCT) Scans. The aim of this study lies in presenting this system as a decision support tool for radiologists in future. The CF features that have been detected and evaluated are Bronchiectasis and Mucus Plugging. This system recognizes Bronchiectasis as the presence of enlarged airways in pulmonary CF-CT slices whereas, Mucus Plugging has been recognized as clusters of high attenuation pixels. The dataset of this study consists of HRCT Scans of five CF patients of varying disease stages. Mean percentages of these CF features that were computed for each intercostal space, starting from the first to the fifth, fairly accurately match the different stages of the disease.
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