title: Automatic workflow for narrow-band laryngeal video stitching.
abstract: In narrow band (NB) laryngeal endoscopy, the clinician usually positions the endoscope near the tissue for a correct inspection of possible vascular pattern alterations, indicative of laryngeal malignancies. The video is usually reviewed many times to refine the diagnosis, resulting in loss of time since the salient frames of the video are mixed with blurred, noisy, and redundant frames caused by the endoscope movements. The aim of this work is to provide to the clinician a unique larynx panorama, obtained through an automatic frame selection strategy to discard non-informative frames. Anisotropic diffusion filtering was exploited to lower the noise level while encouraging the selection of meaningful image features, and a feature-based stitching approach was carried out to generate the panorama. The frame selection strategy, tested on on six pathological NB endoscopic videos, was compared with standard strategies, as uniform and random sampling, showing higher performance of the subsequent stitching procedure, both visually, in terms of vascular structure preservation, and numerically, through a blur estimation metric.
authors.forename: Sara
authors.initials: S
authors.lastname: Moccia
authors.forename: Veronica
authors.initials: V
authors.lastname: Penza
authors.forename: Gabriele Omodeo
authors.initials: GO
authors.lastname: Vanone
authors.forename: Elena
authors.initials: E
authors.lastname: De Momi
authors.forename: Leonardo S
authors.initials: LS
authors.lastname: Mattos
mesh_terms: D016880:Anisotropy; D004724:Endoscopy; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007822:Laryngeal Neoplasms / Q000000981:diagnostic imaging; D007830:Larynx / Q000000981:diagnostic imaging*; D014741:Video Recording; D057188:Workflow