An illumination model of the trachea appearance in videobronchoscopy images

Authors:
Carles Sánchez;Javier Sánchez;Antoni Rosell;Debora Gil
Affiliations:
Comp. Vision Center, Comp. Science Dep., UAB, Spain;Comp. Vision Center, Comp. Science Dep., UAB, Spain;IDIBELL, CIBERES, Pneumology Unit, Hosp. Univ. Bellvitge, Spain;Comp. Vision Center, Comp. Science Dep., UAB, Spain
Venue:
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Year:
2012

Citing 4
Cited 0

The Design and Use of Steerable Filters

IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable registration of bronchoscopic video sequences to CT volumes with guaranteed smooth output

MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Bronchoscopy navigation beyond electromagnetic tracking systems: a novel bronchoscope tracking prototype

MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
ManiSMC: a new method using manifold modeling and sequential monte carlo sampler for boosting navigated bronchoscopy

MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III

Quantified Score

Hi-index	0.00

Visualization

Abstract

Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.