Lung disease stratification using amalgamation of Riesz and Gabor transforms in machine learning framework

• Main Authors: Than, J. C. M., Saba, L., Noor, N. M., Rijal, O. M., Kassim, R. M., Yunus, A., Suri, H. S., Porcu, M., Suri, J. S.
• Format: Article
• Published: Elsevier Ltd 2017
• Subjects: T Technology (General)
• Online Access: http://eprints.utm.my/id/eprint/75954/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027526771&doi=10.1016%2fj.compbiomed.2017.08.014&partnerID=40&md5=c199067fd1793034c2d5f18eafaee780

Lung disease risk stratification is important for both diagnosis and treatment planning, particularly in biopsies and radiation therapy. Manual lung disease risk stratification is challenging because of: (a) large lung data sizes, (b) inter- and intra-observer variability of the lung delineation and...