Construction of 3D lung image morphology using 3D distance regularized level set

• Main Authors: Ng, Chuen Rue, Than, Joel Chia Ming, Rijal, Omar Mohd, Kassim, Rosminah Md, Yunus, Ashari, Noor, Norliza Mohd
• Format: Article
• Published: Asian Research Publishing Network 2019
• Subjects: QA Mathematics; QA75 Electronic computers. Computer science; R Medicine; T Technology (General)
• Online Access: http://eprints.um.edu.my/23852/; http://www.arpnjournals.org/jeas/research_papers/rp_2019/jeas_0119_7534.pdf

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).