TY - GEN
T1 - Fully automated lung volume assessment from MRI in a population-based child cohort study
AU - Ivanovska, Tatyana
AU - Ciet, Pierluigi
AU - Rerez-Rovira, Adria
AU - Nguyen, Anh
AU - Tiddens, Harm
AU - Duijts, Liesbeth
AU - De Bruijne, Marleen
AU - Wörgötter, Florentin
N1 - Publisher Copyright: © 2017 by SCITEPRESS - Science and Technology Publications, Lda.
PY - 2017
Y1 - 2017
N2 - In this work, a framework for fully automated lung extraction from magnetic resonance imaging (MRI) inspiratory data that have been acquired within a on-going epidemiological child cohort study is presented. The method's main steps are intensity inhomogeneity correction, denoising, clustering, airway extraction and lung region refinement. The presented approach produces highly accurate results (Dice coefficients ≤ 95%), when compared to semi-Automatically obtained masks, and has potential to be applied to the whole study data.
AB - In this work, a framework for fully automated lung extraction from magnetic resonance imaging (MRI) inspiratory data that have been acquired within a on-going epidemiological child cohort study is presented. The method's main steps are intensity inhomogeneity correction, denoising, clustering, airway extraction and lung region refinement. The presented approach produces highly accurate results (Dice coefficients ≤ 95%), when compared to semi-Automatically obtained masks, and has potential to be applied to the whole study data.
UR - http://www.scopus.com/inward/record.url?scp=85047879043&partnerID=8YFLogxK
M3 - Conference proceeding
AN - SCOPUS:85047879043
T3 - VISIGRAPP 2017 - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
SP - 53
EP - 58
BT - VISAPP
A2 - Braz, Jose
A2 - Tremeau, Alain
A2 - Imai, Francisco
T2 - 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017
Y2 - 27 February 2017 through 1 March 2017
ER -