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Simeon Petkov; Xavier Carrillo; Petia Radeva; Carlo Gatta |
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Diaphragm border detection in coronary X-ray angiographies: New method and applications |
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2014 |
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Computerized Medical Imaging and Graphics |
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CMIG |
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38 |
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4 |
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296-305 |
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X-ray angiography is widely used in cardiac disease diagnosis during or prior to intravascular interventions. The diaphragm motion and the heart beating induce gray-level changes, which are one of the main obstacles in quantitative analysis of myocardial perfusion. In this paper we focus on detecting the diaphragm border in both single images or whole X-ray angiography sequences. We show that the proposed method outperforms state of the art approaches. We extend a previous publicly available data set, adding new ground truth data. We also compose another set of more challenging images, thus having two separate data sets of increasing difficulty. Finally, we show three applications of our method: (1) a strategy to reduce false positives in vessel enhanced images; (2) a digital diaphragm removal algorithm; (3) an improvement in Myocardial Blush Grade semi-automatic estimation. |
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MILAB; LAMP; 600.079 |
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Admin @ si @ PCR2014 |
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2468 |
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Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; F. Mauri; X. Carillo; T. Kovarnik; C. Wang; H. Chen; T. P. Exarchos; D. I. Fotiadis; F. Destrempes; G. Cloutier; Oriol Pujol; Marina Alberti; E. G. Mendizabal-Ruiz; M. Rivera; T. Aksoy; R. W. Downe; I. A. Kakadiaris |
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Title |
Standardized evaluation methodology and reference database for evaluating IVUS image segmentation |
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Journal Article |
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Year |
2014 |
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Computerized Medical Imaging and Graphics |
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CMIG |
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38 |
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2 |
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70-90 |
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Keywords |
IVUS (intravascular ultrasound); Evaluation framework; Algorithm comparison; Image segmentation |
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This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated.
We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have
been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be
solved. |
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MILAB; LAMP; HuPBA; 600.046; 600.063; 600.079 |
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Admin @ si @ BGC2013 |
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2314 |
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Vacit Oguz Yazici; Long Long Yu; Arnau Ramisa; Luis Herranz; Joost Van de Weijer |
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Title |
Main Product Detection with Graph Networks for Fashion |
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2022 |
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Multimedia Tools and Applications |
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MTAP |
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Computer vision has established a foothold in the online fashion retail industry. Main product detection is a crucial step of vision-based fashion product feed parsing pipelines, focused on identifying the bounding boxes that contain the product being sold in the gallery of images of the product page. The current state-of-the-art approach does not leverage the relations between regions in the image, and treats images of the same product independently, therefore not fully exploiting visual and product contextual information. In this paper, we propose a model that incorporates Graph Convolutional Networks (GCN) that jointly represent all detected bounding boxes in the gallery as nodes. We show that the proposed method is better than the state-of-the-art, especially, when we consider the scenario where title-input is missing at inference time and for cross-dataset evaluation, our method outperforms previous approaches by a large margin. |
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LAMP; MACO; 600.147; 600.167; 600.164; 600.161; 600.141; 601.309 |
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Admin @ si @ YYR2022 |
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3748 |
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Author |
Svebor Karaman; Andrew Bagdanov; Lea Landucci; Gianpaolo D'Amico; Andrea Ferracani; Daniele Pezzatini; Alberto del Bimbo |
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Personalized multimedia content delivery on an interactive table by passive observation of museum visitors |
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2016 |
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Multimedia Tools and Applications |
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MTAP |
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75 |
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7 |
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3787-3811 |
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Computer vision; Video surveillance; Cultural heritage; Multimedia museum; Personalization; Natural interaction; Passive profiling |
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The amount of multimedia data collected in museum databases is growing fast, while the capacity of museums to display information to visitors is acutely limited by physical space. Museums must seek the perfect balance of information given on individual pieces in order to provide sufficient information to aid visitor understanding while maintaining sparse usage of the walls and guaranteeing high appreciation of the exhibit. Moreover, museums often target the interests of average visitors instead of the entire spectrum of different interests each individual visitor might have. Finally, visiting a museum should not be an experience contained in the physical space of the museum but a door opened onto a broader context of related artworks, authors, artistic trends, etc. In this paper we describe the MNEMOSYNE system that attempts to address these issues through a new multimedia museum experience. Based on passive observation, the system builds a profile of the artworks of interest for each visitor. These profiles of interest are then used to drive an interactive table that personalizes multimedia content delivery. The natural user interface on the interactive table uses the visitor’s profile, an ontology of museum content and a recommendation system to personalize exploration of multimedia content. At the end of their visit, the visitor can take home a personalized summary of their visit on a custom mobile application. In this article we describe in detail each component of our approach as well as the first field trials of our prototype system built and deployed at our permanent exhibition space at LeMurate (http://www.lemurate.comune.fi.it/lemurate/) in Florence together with the first results of the evaluation process during the official installation in the National Museum of Bargello (http://www.uffizi.firenze.it/musei/?m=bargello). |
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Springer US |
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1380-7501 |
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LAMP; 601.240; 600.079 |
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Admin @ si @ KBL2016 |
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2520 |
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Author |
Marçal Rusiñol; Volkmar Frinken; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados |
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Title |
Multimodal page classification in administrative document image streams |
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Journal Article |
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2014 |
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International Journal on Document Analysis and Recognition |
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IJDAR |
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17 |
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4 |
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331-341 |
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Digital mail room; Multimodal page classification; Visual and textual document description |
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In this paper, we present a page classification application in a banking workflow. The proposed architecture represents administrative document images by merging visual and textual descriptions. The visual description is based on a hierarchical representation of the pixel intensity distribution. The textual description uses latent semantic analysis to represent document content as a mixture of topics. Several off-the-shelf classifiers and different strategies for combining visual and textual cues have been evaluated. A final step uses an n-gram model of the page stream allowing a finer-grained classification of pages. The proposed method has been tested in a real large-scale environment and we report results on a dataset of 70,000 pages. |
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Springer Berlin Heidelberg |
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1433-2833 |
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DAG; LAMP; 600.056; 600.061; 601.240; 601.223; 600.077; 600.079 |
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Call Number |
Admin @ si @ RFK2014 |
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2523 |
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