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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 dierent 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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Carles Sanchez, Antonio Esteban Lansaque, Agnes Borras, Marta Diez-Ferrer, Antoni Rosell, & Debora Gil. (2017). "Towards a Videobronchoscopy Localization System from Airway Centre Tracking " In 12th International Conference on Computer Vision Theory and Applications (pp. 352–359).
Abstract: Bronchoscopists use fluoroscopy to guide flexible bronchoscopy to the lesion to be biopsied without any kind of incision. Being fluoroscopy an imaging technique based on X-rays, the risk of developmental problems and cancer is increased in those subjects exposed to its application, so minimizing radiation is crucial. Alternative guiding systems such as electromagnetic navigation require specific equipment, increase the cost of the clinical procedure and still require fluoroscopy. In this paper we propose an image based guiding system based on the extraction of airway centres from intra-operative videos. Such anatomical landmarks are matched to the airway centreline extracted from a pre-planned CT to indicate the best path to the nodule. We present a
feasibility study of our navigation system using simulated bronchoscopic videos and a multi-expert validation of landmarks extraction in 3 intra-operative ultrathin explorations.
Keywords: Video-bronchoscopy; Lung cancer diagnosis; Airway lumen detection; Region tracking; Guided bronchoscopy navigation
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Marta Diez-Ferrer, Debora Gil, Elena Carreño, Susana Padrones, Samantha Aso, Vanesa Vicens, et al. (2017). "Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation " . European Respiratory Journal, .
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Mireia Sole, Joan Blanco, Debora Gil, G. Fonseka, Richard Frodsham, Oliver Valero, et al. (2017). "Is there a pattern of Chromosome territoriality along mice spermatogenesis? " In 3rd Spanish MeioNet Meeting Abstract Book (pp. 55–56).
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Mireia Sole, Joan Blanco, Debora Gil, G. Fonseka, Richard Frodsham, Oliver Valero, et al. (2017)." Unraveling the enigmas of chromosome territoriality during spermatogenesis" In IX Jornada del Departament de Biologia Cel•lular, Fisiologia i Immunologia.
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Pau Cano, Alvaro Caravaca, Debora Gil, & Eva Musulen. (2023). "Diagnosis of Helicobacter pylori using AutoEncoders for the Detection of Anomalous Staining Patterns in Immunohistochemistry Images ".
Abstract: This work addresses the detection of Helicobacter pylori a bacterium classified since 1994 as class 1 carcinogen to humans. By its highest specificity and sensitivity, the preferred diagnosis technique is the analysis of histological images with immunohistochemical staining, a process in which certain stained antibodies bind to antigens of the biological element of interest. This analysis is a time demanding task, which is currently done by an expert pathologist that visually inspects the digitized samples.
We propose to use autoencoders to learn latent patterns of healthy tissue and detect H. pylori as an anomaly in image staining. Unlike existing classification approaches, an autoencoder is able to learn patterns in an unsupervised manner (without the need of image annotations) with high performance. In particular, our model has an overall 91% of accuracy with 86\% sensitivity, 96% specificity and 0.97 AUC in the detection of H. pylori.
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Rosa Maria Ortiz, Debora Gil, Elisa Minchole, Marta Diez-Ferrer, & Noelia Cubero de Frutos. (2017). "Classification of Confolcal Endomicroscopy Patterns for Diagnosis of Lung Cancer " In 18th World Conference on Lung Cancer.
Abstract: Confocal Laser Endomicroscopy (CLE) is an emerging imaging technique that allows the in-vivo acquisition of cell patterns of potentially malignant lesions. Such patterns could discriminate between inflammatory and neoplastic lesions and, thus, serve as a first in-vivo biopsy to discard cases that do not actually require a cell biopsy.
The goal of this work is to explore whether CLE images obtained during videobronchoscopy contain enough visual information to discriminate between benign and malign peripheral lesions for lung cancer diagnosis. To do so, we have performed a pilot comparative study with 12 patients (6 adenocarcinoma and 6 benign-inflammatory) using 2 different methods for CLE pattern analysis: visual analysis by 3 experts and a novel methodology that uses graph methods to find patterns in pre-trained feature spaces. Our preliminary results indicate that although visual analysis can only achieve a 60.2% of accuracy, the accuracy of the proposed unsupervised image pattern classification raises to 84.6%.
We conclude that CLE images visual information allow in-vivo detection of neoplastic lesions and graph structural analysis applied to deep-learning feature spaces can achieve competitive results.
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