Standard
Texture Classification in Lung CT Using Local Binary Patterns. / Sørensen, Lauge Emil Borch Laurs; Shaker, Saher B.; de Bruijne, Marleen.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I. red. / D. Metaxas; L. Axel; G. Fichtinger; G. Szekely. Springer, 2008. s. 934-941 (Lecture notes in computer science; Nr. 5241).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Sørensen, LEBL, Shaker, SB
& de Bruijne, M 2008,
Texture Classification in Lung CT Using Local Binary Patterns. i D Metaxas, L Axel, G Fichtinger & G Szekely (red),
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I. Springer, Lecture notes in computer science, nr. 5241, s. 934-941, International Conference on Medical Image Computing and Computer-Assisted Intervention, New York, N.Y., USA,
06/09/2008.
https://doi.org/10.1007/978-3-540-85988-8_111APA
Sørensen, L. E. B. L., Shaker, S. B.
, & de Bruijne, M. (2008).
Texture Classification in Lung CT Using Local Binary Patterns. I D. Metaxas, L. Axel, G. Fichtinger, & G. Szekely (red.),
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I (s. 934-941). Springer. Lecture notes in computer science Nr. 5241
https://doi.org/10.1007/978-3-540-85988-8_111Vancouver
Sørensen LEBL, Shaker SB
, de Bruijne M.
Texture Classification in Lung CT Using Local Binary Patterns. I Metaxas D, Axel L, Fichtinger G, Szekely G, red., Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I. Springer. 2008. s. 934-941. (Lecture notes in computer science; Nr. 5241).
https://doi.org/10.1007/978-3-540-85988-8_111Author
Sørensen, Lauge Emil Borch Laurs ; Shaker, Saher B. ; de Bruijne, Marleen. / Texture Classification in Lung CT Using Local Binary Patterns. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I. red. / D. Metaxas ; L. Axel ; G. Fichtinger ; G. Szekely. Springer, 2008. s. 934-941 (Lecture notes in computer science; Nr. 5241).
Bibtex
@inproceedings{0678b610954111dd86a6000ea68e967b,
title = "Texture Classification in Lung CT Using Local Binary Patterns",
abstract = "Abstract In this paper we propose to use local binary patterns (LBP) as features in a classification framework for classifying different texture patterns in lung computed tomography. Image intensity is included by means of the joint LBP and intensity histogram, and classification is performed using the k nearest neighbor classifier with histogram similarity as distance measure. The proposed method is evaluated on a set of 168 regions of interest comprising normal tissue and different emphysema patterns, and compared to a filter bank based on Gaussian derivatives. The joint LBP and intensity histogram, achieving a classification accuracy of 95.2%, shows superior performance to using the common approach of taking moments of the filter response histograms as features, and slightly better performance than using the full filter response histograms instead. Classification results are better than some of those previously reported in the literature.",
author = "S{\o}rensen, {Lauge Emil Borch Laurs} and Shaker, {Saher B.} and {de Bruijne}, Marleen",
year = "2008",
doi = "10.1007/978-3-540-85988-8_111",
language = "English",
isbn = "9783540859871",
series = "Lecture notes in computer science",
publisher = "Springer",
number = "5241",
pages = "934--941",
editor = "D. Metaxas and L. Axel and G. Fichtinger and G. Szekely",
booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008",
address = "Switzerland",
note = "null ; Conference date: 06-09-2008 Through 10-09-2008",
}
RIS
TY - GEN
T1 - Texture Classification in Lung CT Using Local Binary Patterns
AU - Sørensen, Lauge Emil Borch Laurs
AU - Shaker, Saher B.
AU - de Bruijne, Marleen
N1 - Conference code: 11
PY - 2008
Y1 - 2008
N2 - Abstract In this paper we propose to use local binary patterns (LBP) as features in a classification framework for classifying different texture patterns in lung computed tomography. Image intensity is included by means of the joint LBP and intensity histogram, and classification is performed using the k nearest neighbor classifier with histogram similarity as distance measure. The proposed method is evaluated on a set of 168 regions of interest comprising normal tissue and different emphysema patterns, and compared to a filter bank based on Gaussian derivatives. The joint LBP and intensity histogram, achieving a classification accuracy of 95.2%, shows superior performance to using the common approach of taking moments of the filter response histograms as features, and slightly better performance than using the full filter response histograms instead. Classification results are better than some of those previously reported in the literature.
AB - Abstract In this paper we propose to use local binary patterns (LBP) as features in a classification framework for classifying different texture patterns in lung computed tomography. Image intensity is included by means of the joint LBP and intensity histogram, and classification is performed using the k nearest neighbor classifier with histogram similarity as distance measure. The proposed method is evaluated on a set of 168 regions of interest comprising normal tissue and different emphysema patterns, and compared to a filter bank based on Gaussian derivatives. The joint LBP and intensity histogram, achieving a classification accuracy of 95.2%, shows superior performance to using the common approach of taking moments of the filter response histograms as features, and slightly better performance than using the full filter response histograms instead. Classification results are better than some of those previously reported in the literature.
U2 - 10.1007/978-3-540-85988-8_111
DO - 10.1007/978-3-540-85988-8_111
M3 - Article in proceedings
SN - 9783540859871
T3 - Lecture notes in computer science
SP - 934
EP - 941
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008
A2 - Metaxas, D.
A2 - Axel, L.
A2 - Fichtinger, G.
A2 - Szekely, G.
PB - Springer
Y2 - 6 September 2008 through 10 September 2008
ER -
