Airway Tree Extraction with Locally Optimal Paths

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Airway Tree Extraction with Locally Optimal Paths. / Lo, Pechin Chien Pau; Sporring, Jon; Pedersen, Jesper Johannes Holst; de Bruijne, Marleen.

MICCAI 2009. 2009. p. 51-58.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Lo, PCP, Sporring, J, Pedersen, JJH & de Bruijne, M 2009, Airway Tree Extraction with Locally Optimal Paths. in MICCAI 2009. pp. 51-58, MICCAI 2009, London, United Kingdom, 20/09/2009. https://doi.org/10.1007/978-3-642-04271-3

APA

Lo, P. C. P., Sporring, J., Pedersen, J. J. H., & de Bruijne, M. (2009). Airway Tree Extraction with Locally Optimal Paths. In MICCAI 2009 (pp. 51-58) https://doi.org/10.1007/978-3-642-04271-3

Vancouver

Lo PCP, Sporring J, Pedersen JJH, de Bruijne M. Airway Tree Extraction with Locally Optimal Paths. In MICCAI 2009. 2009. p. 51-58 https://doi.org/10.1007/978-3-642-04271-3

Author

Lo, Pechin Chien Pau ; Sporring, Jon ; Pedersen, Jesper Johannes Holst ; de Bruijne, Marleen. / Airway Tree Extraction with Locally Optimal Paths. MICCAI 2009. 2009. pp. 51-58

Bibtex

@inproceedings{0ffa12b09d3811debc73000ea68e967b,
title = "Airway Tree Extraction with Locally Optimal Paths",
abstract = "This paper proposes a method to extract the airway tree from CT images by continually extending the tree with locally optimal paths. This is in contrast to commonly used region growing based approaches that only search the space of the immediate neighbors. The result is a much more robust method for tree extraction that can overcome local occlusions. The cost function for obtaining the optimal paths takes into account of an airway probability map as well as measures of airway shape and orientation derived from multi-scale Hessian eigen analysis on the airway probability. Significant improvements were achieved compared to a region growing based method, with up to 36% longer trees at a slight increase of false positive rate.",
author = "Lo, {Pechin Chien Pau} and Jon Sporring and Pedersen, {Jesper Johannes Holst} and {de Bruijne}, Marleen",
note = "Udgivelsesdato: 30.09.2009 Volumne: 5762; null ; Conference date: 20-09-2009 Through 24-09-2009",
year = "2009",
doi = "10.1007/978-3-642-04271-3",
language = "English",
pages = "51--58",
booktitle = "MICCAI 2009",

}

RIS

TY - GEN

T1 - Airway Tree Extraction with Locally Optimal Paths

AU - Lo, Pechin Chien Pau

AU - Sporring, Jon

AU - Pedersen, Jesper Johannes Holst

AU - de Bruijne, Marleen

N1 - Conference code: 12

PY - 2009

Y1 - 2009

N2 - This paper proposes a method to extract the airway tree from CT images by continually extending the tree with locally optimal paths. This is in contrast to commonly used region growing based approaches that only search the space of the immediate neighbors. The result is a much more robust method for tree extraction that can overcome local occlusions. The cost function for obtaining the optimal paths takes into account of an airway probability map as well as measures of airway shape and orientation derived from multi-scale Hessian eigen analysis on the airway probability. Significant improvements were achieved compared to a region growing based method, with up to 36% longer trees at a slight increase of false positive rate.

AB - This paper proposes a method to extract the airway tree from CT images by continually extending the tree with locally optimal paths. This is in contrast to commonly used region growing based approaches that only search the space of the immediate neighbors. The result is a much more robust method for tree extraction that can overcome local occlusions. The cost function for obtaining the optimal paths takes into account of an airway probability map as well as measures of airway shape and orientation derived from multi-scale Hessian eigen analysis on the airway probability. Significant improvements were achieved compared to a region growing based method, with up to 36% longer trees at a slight increase of false positive rate.

U2 - 10.1007/978-3-642-04271-3

DO - 10.1007/978-3-642-04271-3

M3 - Article in proceedings

SP - 51

EP - 58

BT - MICCAI 2009

Y2 - 20 September 2009 through 24 September 2009

ER -

ID: 38539447