BRANCH:Bifurcation Recognition for Airway Navigation based on struCtural cHaracteristics

  • Mali ShenEmail author
  • Stamatia Giannarou
  • Pallav L. Shah
  • Guang-Zhong Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10434)


Bronchoscopic navigation is challenging, especially at the level of peripheral airways due to the complicated bronchial structures and the large respiratory motion. The aim of this paper is to propose a localisation approach tailored for navigation in the distal airway branches. Salient regions are detected on the depth maps of video images and CT virtual projections to extract anatomically meaningful areas that represent airway bifurcations. An airway descriptor based on shape context is introduced which encodes both the structural characteristics of the bifurcations and their spatial distribution. The bronchoscopic camera is localised in the airways by minimising the cost of matching the region features in video images to the pre-computed CT depth maps considering both the shape and temporal information. The method has been validated on phantom and in vivo data and the results verify its robustness to tissue deformation and good performance in distal airways.


Airway Bifurcations Depth Map Distal Airways Shape Context Histogram Bronchoscope Camera 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Dr. Giannarou is grateful for the support from the Royal Society (UF140290).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mali Shen
    • 1
    Email author
  • Stamatia Giannarou
    • 1
  • Pallav L. Shah
    • 2
  • Guang-Zhong Yang
    • 1
  1. 1.Hamlyn Centre for Robotic SurgeryImperial College LondonLondonUK
  2. 2.National Heart and Lung InstituteImperial College LondonLondonUK

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