Explaining radiological emphysema subtypes with unsupervised texture prototypes: MESA COPD study

Jie Yang; Elsa D. Angelini; Benjamin M. Smith; John H.M. Austin; Eric A. Hoffman; David A. Bluemke; R. Graham Barr; Andrew F. Laine

doi:10.1007/978-3-319-61188-4_7

Explaining radiological emphysema subtypes with unsupervised texture prototypes: MESA COPD study

Jie Yang, Elsa D. Angelini, Benjamin M. Smith, John H.M. Austin, Eric A. Hoffman, David A. Bluemke, R. Graham Barr, Andrew F. Laine

School of Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Pulmonary emphysema is traditionally subcategorized into three subtypes, which have distinct radiological appearances on computed tomography (CT) and can help with the diagnosis of chronic obstructive pulmonary disease (COPD). Automated texture-based quantification of emphysema subtypes has been successfully implemented via supervised learning of these three emphysema subtypes. In this work, we demonstrate that unsupervised learning on a large heterogeneous database of CT scans can generate texture prototypes that are visually homogeneous and distinct, reproducible across subjects, and capable of predicting accurately the three standard radiological subtypes. These texture prototypes enable automated labeling of lung volumes, and open the way to new interpretations of lung CT scans with finer subtyping of emphysema.

Original language	English (US)
Title of host publication	Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging - MICCAI 2016 International Workshops, MCV and BAMBI, Revised Selected Papers
Editors	Tal Arbel, Georg Langs, Mark Jenkinson, Bjoern Menze, William M. Wells III, Albert C.S. Chung, B. Michael Kelm, Weidong Cai, Albert Montillo, Dimitris Metaxas, M. Jorge Cardoso, Shaoting Zhang, Annemie Ribbens, Henning Muller
Publisher	Springer Verlag
Pages	69-80
Number of pages	12
ISBN (Print)	9783319611877
DOIs	https://doi.org/10.1007/978-3-319-61188-4_7
State	Published - 2017
Event	International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece Duration: Oct 21 2016 → Oct 21 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10081 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/Territory	Greece
City	Athens
Period	10/21/16 → 10/21/16

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-61188-4_7

Cite this

Yang, J., Angelini, E. D., Smith, B. M., Austin, J. H. M., Hoffman, E. A., Bluemke, D. A., Barr, R. G., & Laine, A. F. (2017). Explaining radiological emphysema subtypes with unsupervised texture prototypes: MESA COPD study. In T. Arbel, G. Langs, M. Jenkinson, B. Menze, W. M. Wells III, A. C. S. Chung, B. M. Kelm, W. Cai, A. Montillo, D. Metaxas, M. J. Cardoso, S. Zhang, A. Ribbens, & H. Muller (Eds.), Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging - MICCAI 2016 International Workshops, MCV and BAMBI, Revised Selected Papers (pp. 69-80). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10081 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-61188-4_7

Explaining radiological emphysema subtypes with unsupervised texture prototypes: MESA COPD study. / Yang, Jie; Angelini, Elsa D.; Smith, Benjamin M. et al.
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging - MICCAI 2016 International Workshops, MCV and BAMBI, Revised Selected Papers. ed. / Tal Arbel; Georg Langs; Mark Jenkinson; Bjoern Menze; William M. Wells III; Albert C.S. Chung; B. Michael Kelm; Weidong Cai; Albert Montillo; Dimitris Metaxas; M. Jorge Cardoso; Shaoting Zhang; Annemie Ribbens; Henning Muller. Springer Verlag, 2017. p. 69-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10081 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yang, J, Angelini, ED, Smith, BM, Austin, JHM, Hoffman, EA, Bluemke, DA, Barr, RG & Laine, AF 2017, Explaining radiological emphysema subtypes with unsupervised texture prototypes: MESA COPD study. in T Arbel, G Langs, M Jenkinson, B Menze, WM Wells III, ACS Chung, BM Kelm, W Cai, A Montillo, D Metaxas, MJ Cardoso, S Zhang, A Ribbens & H Muller (eds), Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging - MICCAI 2016 International Workshops, MCV and BAMBI, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10081 LNCS, Springer Verlag, pp. 69-80, International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, Athens, Greece, 10/21/16. https://doi.org/10.1007/978-3-319-61188-4_7

Yang J, Angelini ED, Smith BM, Austin JHM, Hoffman EA, Bluemke DA et al. Explaining radiological emphysema subtypes with unsupervised texture prototypes: MESA COPD study. In Arbel T, Langs G, Jenkinson M, Menze B, Wells III WM, Chung ACS, Kelm BM, Cai W, Montillo A, Metaxas D, Cardoso MJ, Zhang S, Ribbens A, Muller H, editors, Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging - MICCAI 2016 International Workshops, MCV and BAMBI, Revised Selected Papers. Springer Verlag. 2017. p. 69-80. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-61188-4_7

Yang, Jie ; Angelini, Elsa D. ; Smith, Benjamin M. et al. / Explaining radiological emphysema subtypes with unsupervised texture prototypes : MESA COPD study. Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging - MICCAI 2016 International Workshops, MCV and BAMBI, Revised Selected Papers. editor / Tal Arbel ; Georg Langs ; Mark Jenkinson ; Bjoern Menze ; William M. Wells III ; Albert C.S. Chung ; B. Michael Kelm ; Weidong Cai ; Albert Montillo ; Dimitris Metaxas ; M. Jorge Cardoso ; Shaoting Zhang ; Annemie Ribbens ; Henning Muller. Springer Verlag, 2017. pp. 69-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Pulmonary emphysema is traditionally subcategorized into three subtypes, which have distinct radiological appearances on computed tomography (CT) and can help with the diagnosis of chronic obstructive pulmonary disease (COPD). Automated texture-based quantification of emphysema subtypes has been successfully implemented via supervised learning of these three emphysema subtypes. In this work, we demonstrate that unsupervised learning on a large heterogeneous database of CT scans can generate texture prototypes that are visually homogeneous and distinct, reproducible across subjects, and capable of predicting accurately the three standard radiological subtypes. These texture prototypes enable automated labeling of lung volumes, and open the way to new interpretations of lung CT scans with finer subtyping of emphysema.",

author = "Jie Yang and Angelini, {Elsa D.} and Smith, {Benjamin M.} and Austin, {John H.M.} and Hoffman, {Eric A.} and Bluemke, {David A.} and Barr, {R. Graham} and Laine, {Andrew F.}",

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AU - Angelini, Elsa D.

AU - Smith, Benjamin M.

AU - Austin, John H.M.

AU - Hoffman, Eric A.

AU - Bluemke, David A.

AU - Barr, R. Graham

AU - Laine, Andrew F.

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Explaining radiological emphysema subtypes with unsupervised texture prototypes: MESA COPD study

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