Construction of 3D lung image morphology using 3D distance regularized level set
Document Type
Article
Publication Date
1-1-2019
Abstract
The World Health Organization (WHO) has stated in its report that lung disease is a wide spread in Malaysia which caused 2.77% of total death in Malaysia making it the 6th main cause of death in Malaysia. One of the lung diseases included in the list is interstitial lung disease (ILD). ILD includes an extensive group of disorders which leads breathing complications as a result of the alteration and fibrosis to anatomical structures in the alveolar structures. Therefore, diagnosis and analysis of ILD can be performed by segmenting the lung morphology on CT scans images. This study aims to construct a 3D lung image morphology using 3D distance regularized level set evolution (DRLSE). The 3D performance evaluations for normal lungs on average yielded better results than that of ILD lungs with a Dice's similarity coefficient of 93.19%. The constructed lungs from 3D DRSLE has good representation of the segmented normal lungs while suggesting deformities in segmented ILD lungs. © 2006-2019 Asian Research Publishing Network (ARPN).
Keywords
3D segmentation, CT scan, Level set
Divisions
MathematicalSciences
Funders
Universiti Teknologi Malaysia Research University,Ministry of Higher Education Malaysia
Publication Title
ARPN Journal of Engineering and Applied Sciences
Volume
14
Issue
1
Publisher
Asian Research Publishing Network