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Joan Mas, Gemma Sanchez, Josep Llados, & B. Lamiroy. (2007). An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams. In 9th IEEE International Conference on Document Analysis and Recognition (Vol. 1, 452–456).
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Oriol Pujol, Sergio Escalera, & Petia Radeva. (2008). An Incremental Node Embedding Technique for Error Correcting Output Codes. PR - Pattern Recognition, 713–725.
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Petia Radeva, & Enric Marti. (1995). An improved model of snakes for model-based segmentation. In Proceedings of Computer Analysis of Images and Patterns (pp. 515–520).
Abstract: The main advantage of segmentation by snakes consists in its ability to incorporate smoothness constraints on the detected shapes that can occur. Likewise, we propose to model snakes with other properties that reflect the information provided about the object of interest in a different extent. We consider different kinds of snakes, those searching for contours with a certain direction, those preserving an object’s model, those seeking for symmetry, those expanding open, etc. The availability of such a collection of snakes allows not only the more complete use of the knowledge about the segmented object, but also to solve some problems of the existing snakes. Our experiments on segmentation of facial features justify the usefulness of snakes with different properties.
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Carles Sanchez, F. Javier Sanchez, Antoni Rosell, & Debora Gil. (2012). An illumination model of the trachea appearance in videobronchoscopy images. In Image Analysis and Recognition (Vol. 7325, pp. 313–320). LNCS. Springer Berlin Heidelberg.
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.
Keywords: Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation
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A. Martinez, J.R. Serra, Jordi Vitria, & J.B. Subirana. (1997). An Iconic Representation for Image Retrieval.
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Fernando Vilariño, Dimosthenis Karatzas, Marcos Catalan, & Alberto Valcarcel. (2015). An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres. In The White Book on Public Library Network from Diputació de Barcelona.
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David Guillamet, & Jordi Vitria. (2003). An Experimental Evaluation of K-nn for Linear Transforms of Positive Data. In In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science. 2652:317–325.
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David Masip, & Jordi Vitria. (2003). An Experimental Comparision of Dimensionality Reduction for Face Verification Methods.
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Xavier Otazu, Olivier Penacchio, & Xim Cerda-Company. (2015). An excitatory-inhibitory firing rate model accounts for brightness induction, colour induction and visual discomfort. In Barcelona Computational, Cognitive and Systems Neuroscience.
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Mohamed Ali Souibgui, Pau Torras, Jialuo Chen, & Alicia Fornes. (2023). An Evaluation of Handwritten Text Recognition Methods for Historical Ciphered Manuscripts. In 7th International Workshop on Historical Document Imaging and Processing (pp. 7–12).
Abstract: This paper investigates the effectiveness of different deep learning HTR families, including LSTM, Seq2Seq, and transformer-based approaches with self-supervised pretraining, in recognizing ciphered manuscripts from different historical periods and cultures. The goal is to identify the most suitable method or training techniques for recognizing ciphered manuscripts and to provide insights into the challenges and opportunities in this field of research. We evaluate the performance of these models on several datasets of ciphered manuscripts and discuss their results. This study contributes to the development of more accurate and efficient methods for recognizing historical manuscripts for the preservation and dissemination of our cultural heritage.
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Meritxell Vinyals, Arnau Ramisa, & Ricardo Toledo. (2007). An Evaluation of an Object Recognition Schema using Multiple Region Detectors. In Artificial Intelligence Research and Development, 163:213–222, ISBN: 978–1–58603–798–7, Proceedings of the 10th International Conference of the ACIA (CCIA’07).
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Gemma Sanchez, Josep Llados, & K. Tombre. (2001). An Error-Correction Graph Grammar to Recognize Textured Symbols..
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Josep Llados, Gemma Sanchez, & K. Tombre. (2002). An Error-Correction Graph Grammar to Recognize Texture Symbols..
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David Masip, Ludmila I. Kuncheva, & Jordi Vitria. (2005). An ensemble-based method for linear feature extraction for two-class problems. Pattern Analysis and Applications, 8(3): 227–237 (IF: 0.782).
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Antonio Esteban Lansaque. (2019). An Endoscopic Navigation System for Lung Cancer Biopsy (Debora Gil, & Carles Sanchez, Eds.). Ph.D. thesis, Ediciones Graficas Rey, .
Abstract: Lung cancer is one of the most diagnosed cancers among men and women. Actually,
lung cancer accounts for 13% of the total cases with a 5-year global survival
rate in patients. Although Early detection increases survival rate from 38% to 67%, accurate diagnosis remains a challenge. Pathological confirmation requires extracting a sample of the lesion tissue for its biopsy. The preferred procedure for tissue biopsy is called bronchoscopy. A bronchoscopy is an endoscopic technique for the internal exploration of airways which facilitates the performance of minimal invasive interventions with low risk for the patient. Recent advances in bronchoscopic devices have increased their use for minimal invasive diagnostic and intervention procedures, like lung cancer biopsy sampling. Despite the improvement in bronchoscopic device quality, there is a lack of intelligent computational systems for supporting in-vivo clinical decision during examinations. Existing technologies fail to accurately reach the lesion due to several aspects at intervention off-line planning and poor intra-operative guidance at exploration time. Existing guiding systems radiate patients and clinical staff,might be expensive and achieve a suboptimlal 70% of yield boost. Diagnostic yield could be improved reducing radiation and costs by developing intra-operative support systems able to guide the bronchoscopist to the lesion during the intervention. The goal of this PhD thesis is to develop an image-based navigation systemfor intra-operative guidance of bronchoscopists to a target lesion across a path previously planned on a CT-scan. We propose a 3D navigation system which uses the anatomy of video bronchoscopy frames to locate the bronchoscope within the airways. Once the bronchoscope is located, our navigation system is able to indicate the bifurcation which needs to be followed to reach the lesion. In order to facilitate an off-line validation
as realistic as possible, we also present a method for augmenting simulated virtual bronchoscopies with the appearance of intra-operative videos. Experiments performed on augmented and intra-operative videos, prove that our algorithm can be speeded up for an on-line implementation in the operating room.
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