Mr. Antonio Foncubierta-Rodríguez Profile

Antonio Foncubierta-Rodríguez

at ETH Zürich

SPIE Involvement:

Author

Area of Expertise:

Texture analysis , Multidimensional imaging

Publications (9)

Proceedings Article | 20 March 2015 Paper

Pulmonary embolism detection using localized vessel-based features in dual energy CT

Yashin Dicente Cid, Adrien Depeursinge, Antonio Foncubierta Rodríguez, Alexandra Platon, Pierre-Alexandre Poletti, Henning Müller

Proceedings Volume 9414, 941407 (2015) https://doi.org/10.1117/12.2082791

KEYWORDS: Prisms, Image segmentation, Lung, Computed tomography, Dual energy imaging, Signal attenuation, Performance modeling, Iodine, Visualization, Computer aided diagnosis and therapy

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Proceedings Article | 20 March 2015 Paper

Texture classification of anatomical structures in CT using a context-free machine learning approach

Oscar Jiménez del Toro, Antonio Foncubierta-Rodríguez, Adrien Depeursinge, Henning Müller

Proceedings Volume 9414, 94140W (2015) https://doi.org/10.1117/12.2082273

KEYWORDS: Visualization, Lung, Bladder, Spleen, Liver, Medical imaging, Information visualization, Visual analytics, Image segmentation, Matrices

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Proceedings Article | 17 March 2015 Paper

Medical case-based retrieval: integrating query MeSH terms for query-adaptive multi-modal fusion

Alba Seco de Herrera, Antonio Foncubierta-Rodríguez, Henning Müller

Proceedings Volume 9418, 94180S (2015) https://doi.org/10.1117/12.2082028

KEYWORDS: Visualization, Information visualization, Image fusion, Biomedical optics, Feature extraction, Binary data, Neodymium, Medical imaging, Matrices, Medicine

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Proceedings Article | 26 September 2013 Paper

Rotation-covariant visual concept detection using steerable Riesz wavelets and bags of visual words

Adrien Depeursinge, Antonio Foncubierta, Henning Müller, Dimitri Van de Ville

Proceedings Volume 8858, 885816 (2013) https://doi.org/10.1117/12.2023806

KEYWORDS: Visualization, Visual process modeling, Wavelets, Data modeling, Image visualization, Principal component analysis, Visual analytics, Image processing, Radon, Sensors

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Proceedings Article | 29 March 2013 Paper

Region-based volumetric medical image retrieval

Antonio Foncubierta-Rodríguez, Henning Müller, Adrien Depeursinge

Proceedings Volume 8674, 867406 (2013) https://doi.org/10.1117/12.2007971

KEYWORDS: Medical imaging, Wavelets, Human-machine interfaces, Visualization, Image analysis, Sensors, Information visualization, Image retrieval, Lung, 3D image processing

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Proceedings Article | 29 March 2013 Paper

Determining the relative importance of figures in journal articles to find representative images

Henning Müller, Antonio Foncubierta-Rodríguez, Chang Lin, Ivan Eggel

Proceedings Volume 8674, 86740I (2013) https://doi.org/10.1117/12.2007843

KEYWORDS: Visualization, Image retrieval, Medical imaging, Diagnostics, Image visualization, Biomedical optics, Algorithm development, Image processing, Cell phones, Tablets

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When physicians are searching for articles in the medical literature, images of the articles can help determining relevance of the article content for a specific information need. The visual image representation can be an advantage in effectiveness (quality of found articles) and also in efficiency (speed of determining relevance or irrelevance) as many articles can likely be excluded much quicker by looking at a few representative images. In domains such as medical information retrieval, allowing to determine relevance quickly and accurately is an important criterion. This becomes even more important when small interfaces are used as it is frequently the case on mobile phones and tablets to access scientific data whenever information needs arise. In scientific articles many figures are used and particularly in the biomedical literature only a subset may be relevant for determining the relevance of a specific article to an information need. In many cases clinical images can be seen as more important for visual appearance than graphs or histograms that require looking at the context for interpretation. To get a clearer idea of image relevance in articles, a user test with a physician was performed who classified images of biomedical research articles into categories of importance that can subsequently be used to evaluate algorithms that automatically select images as representative examples. The manual sorting of images of 50 journal articles of BioMedCentral with each containing more than 8 figures by importance also allows to derive several rules that determine how to choose images and how to develop algorithms for choosing the most representative images of specific texts. This article describes the user tests and can be a first important step to evaluate automatic tools to select representative images for representing articles and potentially also images in other contexts, for example when representing patient records or other medical concepts when selecting images to represent RadLex terms in tutorials or interactive interfaces for example. This can help to make the image retrieval process more efficient and effective for physicians.

Proceedings Article | 29 March 2013 Paper

Separating compound figures in journal articles to allow for subfigure classification

Ajad Chhatkuli, Antonio Foncubierta-Rodríguez, Dimitrios Markonis, Fabrice Meriaudeau, Henning Müller

Proceedings Volume 8674, 86740J (2013) https://doi.org/10.1117/12.2007897

KEYWORDS: Biomedical optics, Image segmentation, Image classification, Databases, Image filtering, Image retrieval, Algorithm development, Image analysis, Visualization, Medical imaging

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Proceedings Article | 16 February 2012 Paper

Synchronized slice viewing of similar image series

Sharib Ali, Antonio Foncubierta, Adrien Depeursinge, Fabrice Meriaudeau, Osman Ratib, Henning Müller

Proceedings Volume 8319, 83190K (2012) https://doi.org/10.1117/12.911233

KEYWORDS: Image registration, Lung, Brain, Neuroimaging, Cerebellum, Magnetic resonance imaging, Visualization, Image restoration, Computed tomography, Image analysis

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Comparing several series of images is not always easy as the corresponding slices often need to be selected manually. In times where series contain an ever-increasing number of slices this can mean manual work when moving several series to the corresponding slice. Particularly two situations were identified in this context: (1) patients with a large number of image series over time (such as patients with cancers that are monitored) frequently need to compare the series, for example to compare tumor growth over time. Manually adapting two series is possible but with four or more series this can mean loosing time. Having automatically the closest slice by comparing visual similarity also in older series with differing slice thickness and inter slice distance can save time and synchronize the viewing instantly. (2) analyzing visually similar image series of several patients can profit from being viewed in a synchronized way to compare the cases, so when sliding through the slices in one volume, the corresponding slices in the other volumes are shown. This application could be employed after content-based 3D image retrieval has found similar series, for example. Synchronized viewing can help finding or confirming the most relevant cases quickly. To allow for synchronized viewing of several image volumes, the test image series are first registered applying affine transformation for the global registration of images followed by diffeomorphic image registration. Then corresponding slices in the two volumes are estimated based on a visual similarity. Once the registration is finished, the user can subsequently move inside the slices of one volume (reference volume) and can view the corresponding slices in the other volumes. These corresponding slices are obtained after a correspondence match in the registration procedure. These volumes are synchronized in that the slice closest to the original reference volume is shown even when the slice thicknesses or inter slice distances differ, and this is automatically done by comparing the visual image content of the slices. The tool has the potential to help in a variety of situations and it is currently being made available as a plugin for the popular Osirix image viewer.

Proceedings Article | 14 February 2012 Paper

Three dimensional multi-scale visual words for texture-based cerebellum segmentation

Antonio Foncubierta-Rodríguez, Adrien Depeursinge, Laura Gui, Henning Müller

Proceedings Volume 8314, 83142Z (2012) https://doi.org/10.1117/12.911523

KEYWORDS: Cerebellum, Visualization, Image segmentation, Brain, Neuroimaging, Magnetic resonance imaging, Medical imaging, Image analysis, Wavelets, Image retrieval

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Showing 5 of 9 publications

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