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Ole Vilhelm-Larsen, Petia Radeva, & Enric Marti. (1995). Guidelines for choosing optimal parameters of elasticity for snakes. In Computer Analysis Of Images And Patterns (Vol. 970, pp. 106–113). LNCS.
Abstract: This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.
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Ole Larsen, Petia Radeva, & Enric Marti. (1995). Bounds on the optimal elasticity parameters for a snake. Image Analysis and Processing, , 37–42.
Abstract: This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the one actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds.
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Ole Larsen, Petia Radeva, & Enric Marti. (1994). Calculating the Bounds on the Optimal Parameters of Elasticity for a Snake. Denmark: Aalborg University, Laboratory of image Analysis.
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Ognjen Rudovic, & Xavier Roca. (2008). Building Temporale Templates for Human Behaviour Classification. In First International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences BMVC 2008, (79–88).
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Ognjen Rudovic, & Jordi Gonzalez. (2008). Building Temporal Templates for Human Behaviour Classification.
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O.F.Ahmad, Y.Mori, M.Misawa, S.Kudo, J.T.Anderson, & Jorge Bernal. (2021). Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method. END - Endoscopy, 53(9), 893–901.
Abstract: BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. METHODS : An established modified Delphi approach for research priority setting was used. Fifteen international experts, including endoscopists and translational computer scientists/engineers, from nine countries participated in an online survey over 9 months. Questions related to AI implementation in colonoscopy were generated as a long-list in the first round, and then scored in two subsequent rounds to identify the top 10 research questions. RESULTS : The top 10 ranked questions were categorized into five themes. Theme 1: clinical trial design/end points (4 questions), related to optimum trial designs for polyp detection and characterization, determining the optimal end points for evaluation of AI, and demonstrating impact on interval cancer rates. Theme 2: technological developments (3 questions), including improving detection of more challenging and advanced lesions, reduction of false-positive rates, and minimizing latency. Theme 3: clinical adoption/integration (1 question), concerning the effective combination of detection and characterization into one workflow. Theme 4: data access/annotation (1 question), concerning more efficient or automated data annotation methods to reduce the burden on human experts. Theme 5: regulatory approval (1 question), related to making regulatory approval processes more efficient. CONCLUSIONS : This is the first reported international research priority setting exercise for AI in colonoscopy. The study findings should be used as a framework to guide future research with key stakeholders to accelerate the clinical implementation of AI in endoscopy.
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O. Rodriguez, J. Mauri, E Fernandez-Nofrerias, J. Lopez, A. Tovar, V. Valle, et al. (2003). Cuantificacion tridimensional de la longitud de segmentos coronarios a partir de secuencias de ecografia intracoronaria. Revista Española de Cardiologia (IF: 0.959), 56(2), Congreso de las Enfermedades Cardiovasculares.
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O. Rodriguez, J. Mauri, E Fernandez-Nofrerias, J. Lopez, A. Tovar, R. Villuendas, et al. (2003). Modelo fisico para la simulacion de imagenes de ecografia intracoronaria. Revista Española de Cardiologia (IF: 0.959), 56(2), Congreso de las Enfermedades Cardiovasculares.
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O. Rodriguez, J. Mauri, E Fernandez-Nofrerias, C. Garcia, R. Villuendas, A. Tovar, et al. (2003). Model Empiric de Simulacio d Ecografia Intravascular. Revista Societat Catalana de Cardiologia, 4(4):42, XIVe Congres de la Societat Catalana de Cardiologia, .
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O. Rodriguez, J. Mauri, E Fernandez-Nofrerias, A. Tovar, R. Villuendas, V. Valle, et al. (2003). Analisis de texturas mediante la modificacion de un modelo binario local para la segmentacion automatica de secuencias de ecografia intracoronaria. Revista Española de Cardiologia (IF: 0.959), 56(2), Congreso de las Enfermedades Cardiovasculares.
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O. Rodriguez, David Rotger, J. Mauri, E. Fernandez, V. Valle, & Petia Radeva. (2004). Active vessel workstation: three-dimensional reconstruction of coronary arteries by fusion of angiography and intravascular ultrasound.
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O. Fors, Xavier Otazu, & J. Nuñez. (2001). Fusion Mediante Wavelets de Imagenes Spot-pan y del Satelite Tailandes TMSAT..
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O. Fors, J. Nuñez, Xavier Otazu, A. Prades, & Robert D. Cardinal. (2010). Improving the Ability of Image Sensors to Detect Faint Stars and Moving Objects Using Image Deconvolution Techniques. SENS - Sensors, 10(3), 1743–1752.
Abstract: Abstract: In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors.
Keywords: image processing; image deconvolution; faint stars; space debris; wavelet transform
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O. Fors, A. Richichi, Xavier Otazu, & J. Nuñez. (2008). A new wavelet-based approach for the automated treatment of large sets of lunar occultation data. Astronomy and Astrohysics, 297–304.
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Nuria Cirera, Alicia Fornes, Volkmar Frinken, & Josep Llados. (2013). Hybrid grammar language model for handwritten historical documents recognition. In 6th Iberian Conference on Pattern Recognition and Image Analysis (Vol. 7887, pp. 117–124). LNCS. Springer Berlin Heidelberg.
Abstract: In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate.
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