Optimal graph based segmentation using flow lines with application to airway wall segmentation
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Optimal graph based segmentation using flow lines with application to airway wall segmentation. / Petersen, Jens; Nielsen, Mads; Lo, Pechin Chien Pau; Saghir, Zaigham; Dirksen, Asger; de Bruijne, Marleen.
Information Processing in Medical Imaging: 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings. red. / Gábor Székely; Horst K. Hahn. Springer, 2011. s. 49-60 (Lecture notes in computer science, Bind 6801).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Optimal graph based segmentation using flow lines with application to airway wall segmentation
AU - Petersen, Jens
AU - Nielsen, Mads
AU - Lo, Pechin Chien Pau
AU - Saghir, Zaigham
AU - Dirksen, Asger
AU - de Bruijne, Marleen
N1 - Conference code: 22
PY - 2011
Y1 - 2011
N2 - This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited for surfaces with high curvature or complex shapes but the proposed columns, based on properly generated flow lines, which are non-intersecting, guarantee solutions that do not self-intersect and are better able to handle such surfaces. The method is applied to segment human airway walls in computed tomography images. Comparison with manual annotations on 649 cross-sectional images from 15 different subjects shows significantly smaller contour distances and larger area of overlap than are obtained with recently published graph based methods. Airway abnormality measurements obtained with the method on 480 scan pairs from a lung cancer screening trial are reproducible and correlate significantly with lung function.
AB - This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited for surfaces with high curvature or complex shapes but the proposed columns, based on properly generated flow lines, which are non-intersecting, guarantee solutions that do not self-intersect and are better able to handle such surfaces. The method is applied to segment human airway walls in computed tomography images. Comparison with manual annotations on 649 cross-sectional images from 15 different subjects shows significantly smaller contour distances and larger area of overlap than are obtained with recently published graph based methods. Airway abnormality measurements obtained with the method on 480 scan pairs from a lung cancer screening trial are reproducible and correlate significantly with lung function.
U2 - 10.1007/978-3-642-22092-0_5
DO - 10.1007/978-3-642-22092-0_5
M3 - Article in proceedings
SN - 978-3-642-22091-3
T3 - Lecture notes in computer science
SP - 49
EP - 60
BT - Information Processing in Medical Imaging
A2 - Székely, Gábor
A2 - Hahn, Horst K.
PB - Springer
Y2 - 3 July 2011 through 8 July 2011
ER -
ID: 170213214