Optimal graph based segmentation using flow lines with application to airway wall segmentation

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

T2 - 22nd International Conference on Information Processing in Medical Imaging

Y2 - 3 July 2011 through 8 July 2011

ER -