Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability

1. Segmentation of Tracheal Rings in
Videobronchoscopy combining
Geometry and Appearance
Carles Sánchez, Debora Gil, Antoni Rosell ,
Albert Andaluz and F.Javier Sánchez
csanchez@cvc.uab.cat

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OUTLINE
Motivation & Goal
Tracheal Rings Modelling
Tracheal Rings Appearance Model
Tracheal Rings Geometrical Model
Experimental setup
Results
Conclusions & future research

3. 3
Bronchoscopy
machine
Bronchoscope deviceBronchoscopy procedure
WHAT IS A BRONCHOSCOPY?
• HDCC color camera that it is introduced inside the
patient pathway.
• It can be introduced through either nose or mouth.

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 Inside navigation system that provides realistic videos of the interior of the
respiratory pathway.
Trachea scheme Videobronchoscopy
WHAT IS A BRONCHOSCOPY?

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 Detect tumours
 Estimate the percentage of
obstructed airway (stenosis)
 Determine the 3D size
of tracheal stent
Requirements
2D & 3D
measurements from
videos
WHAT IS A BRONCHOSCOPY FOR?
Videobronchoscopy allows
clinicians to:

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HOW DO PHYSICIANS INFER MEASUREMENTS?
 Tracheal rings are the main anatomical structures used to perform
measurements of airway segments size and degree of stenosis.
Healthy segment Obstructed segment
Reference
Ring % obstruction

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Video inspection
- Images in perspective projection
hinder 3D measures
- Requires high experience and
anatomical knowledge of the doctor
CURRENT APPROACHES
Contact procedure
- Invasive procedure that requires
intervention
- Can cause lesions to soft tissues

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EFFICACY OF CURRENT APPROACHES
30%Of wrong measurements that require
repeating the whole intervention
(re-measure & stent replacement)
[S. Norwood, et al., “Incidence of tracheal stenosis and other late complications after percutaneous tracheostomy,” Annals of surgery,
232(2), 233, 2000]
[J.M. Vergnon, et al., “Efficacy of tracheal and bronchial stent placement on respiratory functional tests,” Chest, 107(3),741–746, 1995]
Requires at least two new patient interventions
Physicians need computer vision tools providing
objective measurements

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GOAL
 Automatic detection of tracheal rings using image processing tools
 Challenges:
1) Variety of acquisition
devices: resolution, flexible
or rigid bronchoscope
2) Illumination & acquisition
artifacts : surgical devices,
illumination, blurred images
and camera position
3) Image intensity
appearance is not enough to
discriminate rings to other
structures: veins, carina...

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OUR CONTRIBUTIONS
Model of tracheal rings that combines
their appearance and geometric features
in videobronchoscopic images in order to
minimize de impact of non-tracheal ring
structures

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OUTLINE
Motivation & Goal
Tracheal Rings Modelling
Rings Appearance Model
Rings Geometrical Model
Experimental setup
Results
Conclusions & future research

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TRACHEAL RINGS MODELLING
 Tubular structure in conical projection
 Analyzing Intensity profiles, rings can be described:
 Appearance :
 Ridge-Valley pattern
 Geometry :
 Concentric disposition
 Increasing radial thickness
Real trachea frame Radial intensity profile

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APPEARANCE MODEL
 Detection of valleys as tracheal rings
 Convolve the image with a bank of second derivatives of anisotropic Steerable
Gaussian Filters (SGF) to account for orientation (Ɵ) and scale (σ)
 Account for non-uniform illumination artifacts by the use of a normalized
convolution (NSGF).
σ
[W.T. Freeman, et al. “The design and use of steerable filters,” IEEE Transactions on Pattern analysis and machine intelligence,
13(9),891–906, 1991]

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GEOMETRIC MODEL
 Concentric disposition of rings around the carina
 Change to polar coordinates  Concentric disposition of rings around
carina correspond to almost an horizontal orientation
σmin (farthest ring)
σmax (closest ring)
.
.
.

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 Increasing radial thickness
 It is detected by a decreasing scale profile as rings are traversed from
most external part (L1 plot)
 Structures not belonging to tracheal rings (carina, surgical devices..)
break decreasing profile and are discarded.
GEOMETRICAL MODEL
Higher intensity means larger scales
Image
polar domain
Maximum
response
of NSGF

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Input
Filtering Structure
Preserving
Diffusion Ring
Appearance
Modelling
Ring
Geometric
Modelling
Representation
Space
Preprocess Structure Description
[Sánchez, C., Sánchez, J., Rosell, A., and Gil. Detecting tracheal rings in videobronchoscopy images. CVCRD2011, pages 132–135.]
[Sánchez, C., Sánchez, J., Rosell, A., and Gil, D. An illumination model of the trachea appearance in videobronchoscopy images.
ICIAR2012]
Output
IMAGE PROCESSING SCHEME

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OUTLINE
Motivation & Goal
Tracheal Rings Modelling
Tracheal Rings Appearance Model
Tracheal Rings Geometrical Model
Experimental setup
Results
Conclusions & future research

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EXPERIMENTAL SETUP
 GOAL : Detection of tracheal rings
 Dataset : 4 sequences
Frames B.Type Pthology Resolution
16 Flexible No 192x144
Frames B.Type Pthology Resolution
22 Rigid Yes 512x288
Frames B.Type Pthology Resolution
12 Rigid Yes 360x288
Frames B.Type Pthology Resolution
10 Flexible No 512x288

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EXPERIMENTAL SETUP
 GOAL : Detection of tracheal rings
 Dataset : 4 sequences
 Results by comparison with manual segmentation by medical expert
 Two different experts in order to account inter-observer variability.
 Accounting Sensitivity (Sens) and Precision (Prec) 1 pixel distance away
from manual curves.
 Mean ±standard deviation for each sequence.
 Wilcoxon signed-rang test to compute the
differences between experts and automatic.

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OUTLINE
Motivation & Goal
Tracheal Rings Modelling
Tracheal Rings Appearance Model
Tracheal Rings Geometrical Model
Experimental setup
Results
Conclusions & future research

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RESULTS – Quantitative
COMPARISON (AUT)
AUTO VS. MANUALS
COMPARISON (IO)
MANUAL VS. MANUAL
Validation Sens Prec Sens Prec
Seq1 [71.16,96.20] [57.67,80.08] [71.21, 99.61] [71.70, 98.87]
Wilcoxon( CI, p-val)
Validation Sens (CI) Sens (p-val) Prec (CI) Prec (p-val)
Seq1 [−11.75, 4.74] 0.4856 [−23.58, −12.08] 0.0004
 Wilcoxon test : confidence intervals of the difference (AUT-IO)
 P-val ~ 0 : indicates that differences are significant.
 Else : Automatic segmentations are detecting as manual ones.

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RESULTS – Quantitative
COMPARISON (AUT)
AUTO VS. MANUALS
COMPARISON (IO)
MANUAL VS. MANUAL
Validation Sens Prec Sens Prec
Seq1 [71.16,96.20] [57.67,80.08] [71.21, 99.61] [71.70, 98.87]
Seq2 [66.11,94.01] [52.22,67.72] [56.13, 72.84] [56.32, 72.59]
Seq3 [60.29,83.53] [51.25,60.97] [59.56, 78.41] [59.70, 78.23]
Seq4 [57.87,92.72] [51.16,75.90] [62.66, 86.35] [62.84, 86.08]
Wilcoxon( CI, p-val)
Validation Sens Prec
Seq1 [−11.75, 4.74], 0.4856 [−23.58, −12.08], 0.0004
Seq2 [7.94, 24.14], 0.0006 [−11.06, −1.48], 0.0183
Seq3 [−0.70, 6.55], 0.3481 [−17.09, −8.61], 0.00009
Seq4 [−6.70, 8.27], 0.9031 [−18.18, −3.68], 0.0056

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RESULTS – Qualitative
 All rings are detected (sensitivity within inter-observer range)
 Some extra structures dropping precision
 Rigid artifacts
 Some rings well detected but not identified by the expert
(external and internal ones)

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RESULTS – IO Variability
 Some inner and outer rings not identified by experts.
 Continues lines because of the doctor knowledge

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RESULTS vs. Basic intensity aproches
Basic intensity approaches Geometry and appearance model

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OUTLINE
Motivation & Goal
Tracheal Rings Modelling
Tracheal Rings Appearance Model
Tracheal Rings Geometrical Model
Experimental setup
Results
Conclusions & future research

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CONCLUSIONS & FUTURE RESEARCH
 Tracheal ring detection for stenosi assessment is a challenging task and
novel area.
 We have introduced a Geometrical Appearance model for tracheal ring
detection.
 Our geometric structure avoids any response at the carina and minimizes
the impact of alien structures (veins, blood, surgical devices...).
 Results prove that our detection can retrieve most clinically relevant tracheal
rings
 Enlarge the dataset including more types of pathologies, rigid and flexible
 Suppress all responses in the rigid artifacts
 Close the detected rings
CONCLUSIONS:
FUTURE RESEARCH:

28. Segmentation of Tracheal Rings in
Videobronchoscopy combining
Geometry and Appearance
Carles Sánchez, Debora Gil, Antoni Rosell ,
Albert Andaluz and F.Javier Sánchez
csanchez@cvc.uab.cat
THANKS FOR YOUR ATTENTION!!
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