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A. M. Here, B. C. Lopez, Debora Gil, J. J. Camarero, & Jordi Martinez-Vilalta. (2013). "A new software to analyse wood anatomical features in conifer species " In International Symposium on Wood Structure in Plant Biology and Ecology.
Abstract: International Symposium on Wood Structure in Plant Biology and Ecology
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Sergio Vera, Miguel Angel Gonzalez Ballester, & Debora Gil. (2013). "Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition " In 16th International Conference on Medical Image Computing and Computer Assisted Intervention.
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Sergio Vera, Debora Gil, & Miguel Angel Gonzalez Ballester. (2014). "Anatomical parameterization for volumetric meshing of the liver " In SPIE – Medical Imaging (Vol. 9036).
Abstract: A coordinate system describing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specific anatomical landmarks, the coordinate system allows integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric coordinate systems over the surface of anatomical shapes, given their flexibility to set values
at specific locations through boundary conditions. However, most of the existing implementations in medical imaging restrict to either anatomical surfaces, or the depth coordinate with boundary conditions is given at sites
of limited geometric diversity. In this paper we present a method for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the
volume medial surface. We have applied the methodology to define a common reference system for the liver shape and functional anatomy. This reference system sets a solid base for creating anatomical models of the patient’s liver, and allows comparing livers from several patients in a common framework of reference.
Keywords: Coordinate System; Anatomy Modeling; Parameterization
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Carles Sanchez, Debora Gil, R. Tazi, Jorge Bernal, Y. Ruiz, L. Planas, et al. (2015)." Quasi-real time digital assessment of Central Airway Obstruction" In 3rd European congress for bronchology and interventional pulmonology ECBIP2015.
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Hanne Kause, Patricia Marquez, Andrea Fuster, Aura Hernandez-Sabate, Luc Florack, Debora Gil, et al. (2015)." Quality Assessment of Optical Flow in Tagging MRI" In 5th Dutch Bio-Medical Engineering Conference BME2015.
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Gloria Fernandez Esparrach, Jorge Bernal, Cristina Rodriguez de Miguel, Debora Gil, Fernando Vilariño, Henry Cordova, et al. (2015). "Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps " In Proceedings of 23 United European- UEG Week 2015.
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Antonio Esteban Lansaque, Carles Sanchez, Agnes Borras, Marta Diez-Ferrer, Antoni Rosell, & Debora Gil. (2016). "Stable Airway Center Tracking for Bronchoscopic Navigation " In 28th Conference of the international Society for Medical Innovation and Technology.
Abstract: Bronchoscopists use X‐ray fluoroscopy to guide bronchoscopes to the lesion to be biopsied without any kind of incisions. Reducing exposure to X‐ray is important for both patients and doctors but alternatives like electromagnetic navigation require specific equipment and increase the cost of the clinical procedure. We propose a guiding system based on the extraction of airway centers from intra‐operative videos. Such anatomical landmarks could be
matched to the airway centerline extracted from a pre‐planned CT to indicate the best path to the lesion. We present an extraction of lumen centers
from intra‐operative videos based on tracking of maximal stable regions of energy maps.
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Antonio Esteban Lansaque, Carles Sanchez, Agnes Borras, Marta Diez-Ferrer, Antoni Rosell, & Debora Gil. (2016). "Stable Anatomical Structure Tracking for video-bronchoscopy Navigation " In 19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops.
Abstract: Bronchoscopy allows to examine the patient airways for detection of lesions and sampling of tissues without surgery. A main drawback in lung cancer diagnosis is the diculty to check whether the exploration is following the correct path to the nodule that has to be biopsied. The most extended guidance uses uoroscopy which implies repeated radiation of clinical sta and patients. Alternatives such as virtual bronchoscopy or electromagnetic navigation are very expensive and not completely robust to blood, mocus or deformations as to be extensively used. We propose a method that extracts and tracks stable lumen regions at di erent levels of the bronchial tree. The tracked regions are stored in a tree that encodes the anatomical structure of the scene which can be useful to retrieve the path to the lesion that the clinician should follow to do the biopsy. We present a multi-expert validation of our anatomical landmark extraction in 3 intra-operative ultrathin explorations.
Keywords: Lung cancer diagnosis; video-bronchoscopy; airway lumen detection; region tracking
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Mireia Sole, Joan Blanco, Debora Gil, Oliver Valero, G. Fonseka, M. Lawrie, et al. (2017). "Chromosome Territories in Mice Spermatogenesis: A new three-dimensional methodology of study " In 11th European CytoGenesis Conference.
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Carles Sanchez, Debora Gil, T. Gache, N. Koufos, Marta Diez-Ferrer, & Antoni Rosell. (2016). "SENSA: a System for Endoscopic Stenosis Assessment " In 28th Conference of the international Society for Medical Innovation and Technology.
Abstract: Documenting the severity of a static or dynamic Central Airway Obstruction (CAO) is crucial to establish proper diagnosis and treatment, predict possible treatment effects and better follow-up the patients. The subjective visual evaluation of a stenosis during video-bronchoscopy still remains the most common way to assess a CAO in spite of a consensus among experts for a need to standardize all calculations [1].
The Computer Vision Center in cooperation with the «Hospital de Bellvitge», has developed a System for Endoscopic Stenosis Assessment (SENSA), which computes CAO directly by analyzing standard bronchoscopic data without the need of using other imaging tecnologies.
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