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International Workshop on Computer-Assisted and Robotic Endoscopy

Workshop on Clinical Image-Based Procedures

International Workshop on OR 2.0 Context-Aware Operating Theaters

International Workshop on Skin Image Analysis

CARE 2018, CLIP 2018, OR 2.0 2018, ISIC 2018: OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis pp 214–222Cite as

Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy

Part of the Lecture Notes in Computer Science book series (LNIP,volume 11041)

Abstract

Bronchoscopy examinations allow biopsy of pulmonary nodules with minimum risk for the patient. Even for experienced bronchoscopists, it is difficult to guide the bronchoscope to most distal lesions and obtain an accurate diagnosis. This paper presents an image-based codification of the bronchial anatomy for bronchoscopy biopsy guiding. The 3D anatomy of each patient is codified as a binary tree with nodes representing bronchial levels and edges labeled using their position on images projecting the 3D anatomy from a set of branching points. The paths from the root to leaves provide a codification of navigation routes with spatially consistent labels according to the anatomy observes in video bronchoscopy explorations. We evaluate our labeling approach as a guiding system in terms of the number of bronchial levels correctly codified, also in the number of labels-based instructions correctly supplied, using generalized mixed models and computer-generated data. Results obtained for three independent observers prove the consistency and reproducibility of our guiding system. We trust that our codification based on viewer’s projection might be used as a foundation for the navigation process in Virtual Bronchoscopy systems.

Keywords

  • Biopsy guiding
  • Bronchoscopy
  • Lung biopsy
  • Intervention guiding
  • Airway codification

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Acknowledgments

This work was supported by Catalan, Spanish and European projects DPI2015-65286-R, 2014-SGR-1470, CERCA Programme/Generalitat de Catalunya. Also, the first author holds the fellowship number BES-2016-078042 granted by the Ministry of Economy, Industry and Competitiveness, Spain. A Titan X Pascal was used for this research, donated by NVIDIA. Debora Gil is part of the Serra Hunter programme.

Author information

Authors and Affiliations

  1. Computer Vision Center, Autonomous University of Barcelona, 08193, Barcelona, Spain

    Esmitt Ramírez, Carles Sánchez, Agnés Borràs & Debora Gil

  2. Bellvitge University Hospital, L’Hospitalet de Llobregat, 08907, Barcelona, Spain

    Marta Diez-Ferrer & Antoni Rosell

Authors
  1. Esmitt Ramírez
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  2. Carles Sánchez
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  3. Agnés Borràs
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  4. Marta Diez-Ferrer
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  5. Antoni Rosell
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  6. Debora Gil
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Corresponding author

Correspondence to Esmitt Ramírez .

Editor information

Editors and Affiliations

  1. University College London, London, UK

    Danail Stoyanov

  2. University of Leeds, Leeds, UK

    Dr. Zeike Taylor

  3. University of Rennes, Rennes, France

    Duygu Sarikaya

  4. University of Western Ontario, London, ON, Canada

    Jonathan McLeod

  5. Universitat Pompeu Fabra, Barcelona, Spain

    Miguel Angel González Ballester

  6. IBM Research, Yorktown Heights, NY, USA

    Noel C.F. Codella

  7. Sunnybrook Health Science Centre, Toronto, ON, Canada

    Anne Martel

  8. German Cancer Research Center, Heidelberg, Baden-Württemberg, Germany

    Lena Maier-Hein

  9. Johns Hopkins University, Baltimore, USA

    Anand Malpani

  10. Harvard Medical School, Boston, USA

    Marco A. Zenati

  11. University of Western Ontario, London, Canada

    Sandrine De Ribaupierre

  12. Xiamen University, Xiamen, China

    Luo Xiongbiao

  13. IRCAD, Strasbourg, France

    Toby Collins

  14. KUKA Laboratories GmbH, Augsburg, Germany

    Tobias Reichl

  15. Aachen University of Applied Sciences, Julich, Nordrhein-Westfalen, Germany

    Klaus Drechsler

  16. Fraunhofer IDM@NTU, Singapore, Singapore

    Marius Erdt

  17. Children's National Health System, Washington, D.C., DC, USA

    Marius George Linguraru

  18. Fraunhofer IGD, Darmstadt, Hessen, Germany

    Cristina Oyarzun Laura

  19. Children's National Health System, Washington, D.C., DC, USA

    Raj Shekhar

  20. Fraunhofer IGD, Darmstadt, Hessen, Germany

    Stefan Wesarg

  21. University of Central Arkansas, Conway, USA

    M. Emre Celebi

  22. Rutgers University, Piscataway, USA

    Kristin Dana

  23. Memorial Sloan Kettering Cancer Center, New York, USA

    Allan Halpern

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Ramírez, E., Sánchez, C., Borràs, A., Diez-Ferrer, M., Rosell, A., Gil, D. (2018). Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy. In: , et al. OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis. CARE CLIP OR 2.0 ISIC 2018 2018 2018 2018. Lecture Notes in Computer Science(), vol 11041. Springer, Cham. https://doi.org/10.1007/978-3-030-01201-4_23

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  • DOI: https://doi.org/10.1007/978-3-030-01201-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01200-7

  • Online ISBN: 978-3-030-01201-4

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