|Home||<< 1 >>|
Esmitt Ramirez, Carles Sanchez, Agnes Borras, Marta Diez-Ferrer, Antoni Rosell, & Debora Gil. (2018). Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy. In OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis (Vol. 11041). LNCS.
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