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Author |
Fernando Vilariño |
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Title |
Unveiling the Social Impact of AI |
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Conference Article |
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2020 |
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Workshop at Digital Living Lab Days Conference |
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September 2020 |
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MV; DAG; 600.121; 600.140;SIAI |
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Admin @ si @ Vil2020 |
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3459 |
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Author |
Fernando Vilariño |
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Title |
Library Living Lab, Numérisation 3D des chapiteaux du cloître de Saint-Cugat : des citoyens co- créant le nouveau patrimoine culturel numérique |
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Conference Article |
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2019 |
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Intersectorialité et approche Living Labs. Entretiens Jacques-Cartier |
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Montreal; Canada; December 2019 |
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MV; DAG; 600.140; 600.121;SIAI |
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Admin @ si @ Vil2019a |
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3457 |
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Author |
Fernando Vilariño |
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Title |
Public Libraries Exploring how technology transforms the cultural experience of people |
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Conference Article |
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2019 |
Publication |
Workshop on Social Impact of AI. Open Living Lab Days Conference. |
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Thessaloniki; Grecia; September 2019 |
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MV; DAG; 600.140; 600.121;SIAI |
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Admin @ si @ Vil2019b |
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3458 |
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Author |
Fernando Vilariño |
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Title |
3D Scanning of Capitals at Library Living Lab |
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2019 |
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“Living Lab Projects 2019”. ENoLL. |
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MV; DAG; 600.140; 600.121;SIAI |
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Admin @ si @ Vil2019c |
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3463 |
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Author |
Fernando Vilariño; Dimosthenis Karatzas |
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Title |
The Library Living Lab |
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Conference Article |
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2015 |
Publication |
Open Living Lab Days |
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Istanbul; Turkey; August 2015 |
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OLLD |
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MV; DAG;SIAI |
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Admin @ si @ViK2015 |
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2797 |
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Author |
Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel |
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Title |
An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres |
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Book Chapter |
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2015 |
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The White Book on Public Library Network from Diputació de Barcelona |
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MV; DAG;SIAI |
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Admin @ si @VKC2015 |
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2798 |
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Author |
Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez |
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Title |
Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis |
Type |
Conference Article |
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Year |
2014 |
Publication |
1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy |
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8899 |
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1-10 |
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Keywords |
Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps |
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Abstract |
In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-13409-3 |
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CARE |
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MV; IAM; 600.044; 600.047; 600.060; 600.075 |
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Admin @ si @ BGS2014b |
Serial |
2503 |
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Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |
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Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
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Conference Article |
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Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
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8361 |
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31-38 |
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Lumen centre detection; Bronchoscopy; Colonoscopy |
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We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). |
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Nagoya; Japan; September 2013 |
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Springer International Publishing |
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Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus |
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978-3-319-05665-4 |
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800 |
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CLIP |
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MV; IAM; 600.047; 600.044; 600.060 |
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no |
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Call Number |
Admin @ si @ SBG2013 |
Serial |
2302 |
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Author |
Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño |
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Title |
WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians |
Type |
Journal Article |
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Year |
2015 |
Publication |
Computerized Medical Imaging and Graphics |
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CMIG |
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43 |
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99-111 |
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Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection |
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We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice. |
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0895-6111 |
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MV; IAM; 600.047; 600.060; 600.075;SIAI |
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Admin @ si @ BSF2015 |
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2609 |
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Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; I.Araujo ; Maria Lopez Ceron; J.Llach; F. Javier Sanchez |
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Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps |
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2015 |
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Proceedings of 23 United European- UEG Week 2015 |
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UEG |
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MV; IAM; 600.075;SIAI |
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Admin @ si @ FBR2015 |
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2732 |
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Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; Isis Ara |
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Title |
Utilidad de la visión por computador para la localización de pólipos pequeños y planos |
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Conference Article |
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2016 |
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XIX Reunión Nacional de la Asociación Española de Gastroenterología, Gastroenterology Hepatology |
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39 |
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2 |
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94 |
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Madrid (Spain) |
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AEGASTRO |
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MV; IAM; 600.097;SIAI |
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Admin @ si @FBR2016 |
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2779 |
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Arturo Fuentes; F. Javier Sanchez; Thomas Voncina; Jorge Bernal |
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Title |
LAMV: Learning to Predict Where Spectators Look in Live Music Performances |
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Conference Article |
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2021 |
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16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
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5 |
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500-507 |
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The advent of artificial intelligence has supposed an evolution on how different daily work tasks are performed. The analysis of cultural content has seen a huge boost by the development of computer-assisted methods that allows easy and transparent data access. In our case, we deal with the automation of the production of live shows, like music concerts, aiming to develop a system that can indicate the producer which camera to show based on what each of them is showing. In this context, we consider that is essential to understand where spectators look and what they are interested in so the computational method can learn from this information. The work that we present here shows the results of a first preliminary study in which we compare areas of interest defined by human beings and those indicated by an automatic system. Our system is based on the extraction of motion textures from dynamic Spatio-Temporal Volumes (STV) and then analyzing the patterns by means of texture analysis techniques. We validate our approach over several video sequences that have been labeled by 16 different experts. Our method is able to match those relevant areas identified by the experts, achieving recall scores higher than 80% when a distance of 80 pixels between method and ground truth is considered. Current performance shows promise when detecting abnormal peaks and movement trends. |
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Virtual; February 2021 |
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VISIGRAPP |
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MV; ISE; 600.119; |
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Admin @ si @ FSV2021 |
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3570 |
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Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Maroua Hammami; Gloria Fernandez Esparrach; Xavier Dray; Olivier Romain; F. Javier Sanchez; Aymeric Histace |
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Real-Time Polyp Detection in Colonoscopy Videos: A Preliminary Study For Adapting Still Frame-based Methodology To Video Sequences Analysis |
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Conference Article |
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2017 |
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31st International Congress and Exhibition on Computer Assisted Radiology and Surgery |
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Barcelona; Spain; June 2017 |
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CARS |
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MV; no menciona |
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Admin @ si @ ABS2017 |
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2947 |
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Patrick Brandao; O. Zisimopoulos; E. Mazomenos; G. Ciutib; Jorge Bernal; M. Visentini-Scarzanell; A. Menciassi; P. Dario; A. Koulaouzidis; A. Arezzo; D.J. Hawkes; D. Stoyanov |
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Towards a computed-aided diagnosis system in colonoscopy: Automatic polyp segmentation using convolution neural networks |
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2018 |
Publication |
Journal of Medical Robotics Research |
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JMRR |
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3 |
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2 |
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convolutional neural networks; colonoscopy; computer aided diagnosis |
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Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), ne-tune them and study their capabilities for polyp segmentation and detection. We additionally use Shape-from-Shading (SfS) to recover depth and provide a richer representation of the tissue's structure in colonoscopy images. Depth is
incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation IU of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp
detection, the top performing models we propose surpass the current state of the art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the rst work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance. |
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MV; no menciona |
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no |
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BZM2018 |
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2976 |
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Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Maroua Hammami; Gloria Fernandez Esparrach; Xavier Dray; Olivier Romain; F. Javier Sanchez; Aymeric Histace |
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Title |
Clinical Usability Quantification Of a Real-Time Polyp Detection Method In Videocolonoscopy |
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Conference Article |
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Year |
2017 |
Publication |
25th United European Gastroenterology Week |
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Address |
Barcelona, October 2017 |
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ESGE |
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Notes |
MV; no menciona |
Approved |
no |
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Call Number |
Admin @ si @ ABS2017c |
Serial |
2978 |
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