Records |
Author |
Carles Fernandez; Jordi Gonzalez |
Title |
Ontology for Semantic Integration in a Cognitive Surveillance System |
Type |
Conference Article |
Year |
2007 |
Publication |
Semantic Multimedia, 2nd International Conference on Semantics and Digital Media Technologies |
Abbreviated Journal |
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Volume |
4816 |
Issue |
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Pages |
263–263 |
Keywords |
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Abstract |
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Address |
Genova (Italy) |
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LNCS |
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Conference |
SAMT’07 |
Notes |
ISE |
Approved |
no |
Call Number |
ISE @ ise @ FeG2007 |
Serial |
919 |
Permanent link to this record |
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Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |
Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
Type |
Conference Article |
Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
Abbreviated Journal |
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Volume |
8361 |
Issue |
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Pages |
31-38 |
Keywords |
Lumen centre detection; Bronchoscopy; Colonoscopy |
Abstract |
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 %). |
Address |
Nagoya; Japan; September 2013 |
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Thesis |
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Publisher |
Springer International Publishing |
Place of Publication |
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Editor |
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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LNCS |
Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-3-319-05665-4 |
Medium |
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Area |
800 |
Expedition |
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Conference |
CLIP |
Notes |
MV; IAM; 600.047; 600.044; 600.060 |
Approved |
no |
Call Number |
Admin @ si @ SBG2013 |
Serial |
2302 |
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Author |
David Masip; Jordi Vitria |
Title |
Real Time Face Detection and Verification for Uncontrolled Environments |
Type |
Miscellaneous |
Year |
2004 |
Publication |
Second COST 275 Workshop Biometrics on the Internet: Fundamentals, Advances and Applications, 55–58. |
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Address |
Vigo |
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Notes |
OR;MV |
Approved |
no |
Call Number |
BCNPCL @ bcnpcl @ MaV2004a |
Serial |
446 |
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Author |
Xavier Otazu; Olivier Penacchio; Xim Cerda-Company |
Title |
Brightness and colour induction through contextual influences in V1 |
Type |
Conference Article |
Year |
2015 |
Publication |
Scottish Vision Group 2015 SGV2015 |
Abbreviated Journal |
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Volume |
12 |
Issue |
9 |
Pages |
1208-2012 |
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Abstract |
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Address |
Carnoustie; Scotland; March 2015 |
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Conference |
SGV |
Notes |
NEUROBIT; |
Approved |
no |
Call Number |
Admin @ si @ OPC2015a |
Serial |
2632 |
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Author |
Victor M. Campello; Carlos Martin-Isla; Cristian Izquierdo; Andrea Guala; Jose F. Rodriguez Palomares; David Vilades; Martin L. Descalzo; Mahir Karakas; Ersin Cavus; Zahra Zahra Raisi-Estabragh; Steffen E. Petersen; Sergio Escalera; Santiago Segui; Karim Lekadir |
Title |
Minimising multi-centre radiomics variability through image normalisation: a pilot study |
Type |
Journal Article |
Year |
2022 |
Publication |
Scientific Reports |
Abbreviated Journal |
ScR |
Volume |
12 |
Issue |
1 |
Pages |
12532 |
Keywords |
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Abstract |
Radiomics is an emerging technique for the quantification of imaging data that has recently shown great promise for deeper phenotyping of cardiovascular disease. Thus far, the technique has been mostly applied in single-centre studies. However, one of the main difficulties in multi-centre imaging studies is the inherent variability of image characteristics due to centre differences. In this paper, a comprehensive analysis of radiomics variability under several image- and feature-based normalisation techniques was conducted using a multi-centre cardiovascular magnetic resonance dataset. 218 subjects divided into healthy (n = 112) and hypertrophic cardiomyopathy (n = 106, HCM) groups from five different centres were considered. First and second order texture radiomic features were extracted from three regions of interest, namely the left and right ventricular cavities and the left ventricular myocardium. Two methods were used to assess features’ variability. First, feature distributions were compared across centres to obtain a distribution similarity index. Second, two classification tasks were proposed to assess: (1) the amount of centre-related information encoded in normalised features (centre identification) and (2) the generalisation ability for a classification model when trained on these features (healthy versus HCM classification). The results showed that the feature-based harmonisation technique ComBat is able to remove the variability introduced by centre information from radiomic features, at the expense of slightly degrading classification performance. Piecewise linear histogram matching normalisation gave features with greater generalisation ability for classification ( balanced accuracy in between 0.78 ± 0.08 and 0.79 ± 0.09). Models trained with features from images without normalisation showed the worst performance overall ( balanced accuracy in between 0.45 ± 0.28 and 0.60 ± 0.22). In conclusion, centre-related information removal did not imply good generalisation ability for classification. |
Address |
2022/07/22 |
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Publisher |
Springer Nature |
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Notes |
HuPBA |
Approved |
no |
Call Number |
Admin @ si @ CMI2022 |
Serial |
3749 |
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Author |
Iban Berganzo-Besga; Hector A. Orengo; Felipe Lumbreras; Aftab Alam; Rosie Campbell; Petrus J Gerrits; Jonas Gregorio de Souza; Afifa Khan; Maria Suarez Moreno; Jack Tomaney; Rebecca C Roberts; Cameron A Petrie |
Title |
Curriculum learning-based strategy for low-density archaeological mound detection from historical maps in India and Pakistan |
Type |
Journal Article |
Year |
2023 |
Publication |
Scientific Reports |
Abbreviated Journal |
ScR |
Volume |
13 |
Issue |
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Pages |
11257 |
Keywords |
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Abstract |
This paper presents two algorithms for the large-scale automatic detection and instance segmentation of potential archaeological mounds on historical maps. Historical maps present a unique source of information for the reconstruction of ancient landscapes. The last 100 years have seen unprecedented landscape modifications with the introduction and large-scale implementation of mechanised agriculture, channel-based irrigation schemes, and urban expansion to name but a few. Historical maps offer a window onto disappearing landscapes where many historical and archaeological elements that no longer exist today are depicted. The algorithms focus on the detection and shape extraction of mound features with high probability of being archaeological settlements, mounds being one of the most commonly documented archaeological features to be found in the Survey of India historical map series, although not necessarily recognised as such at the time of surveying. Mound features with high archaeological potential are most commonly depicted through hachures or contour-equivalent form-lines, therefore, an algorithm has been designed to detect each of those features. Our proposed approach addresses two of the most common issues in archaeological automated survey, the low-density of archaeological features to be detected, and the small amount of training data available. It has been applied to all types of maps available of the historic 1″ to 1-mile series, thus increasing the complexity of the detection. Moreover, the inclusion of synthetic data, along with a Curriculum Learning strategy, has allowed the algorithm to better understand what the mound features look like. Likewise, a series of filters based on topographic setting, form, and size have been applied to improve the accuracy of the models. The resulting algorithms have a recall value of 52.61% and a precision of 82.31% for the hachure mounds, and a recall value of 70.80% and a precision of 70.29% for the form-line mounds, which allowed the detection of nearly 6000 mound features over an area of 470,500 km2, the largest such approach to have ever been applied. If we restrict our focus to the maps most similar to those used in the algorithm training, we reach recall values greater than 60% and precision values greater than 90%. This approach has shown the potential to implement an adaptive algorithm that allows, after a small amount of retraining with data detected from a new map, a better general mound feature detection in the same map. |
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Conference |
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Notes |
MSIAU |
Approved |
no |
Call Number |
Admin @ si @ BOL2023 |
Serial |
3976 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
Title |
Stereo Vision Camera Pose Estimation for On-Board Applications |
Type |
Book Chapter |
Year |
2007 |
Publication |
Scene Reconstruction, Pose Estimation and Traking |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
39-50 |
Keywords |
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Abstract |
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Address |
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Corporate Author |
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Thesis |
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Publisher |
Rustam Stolking |
Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Edition |
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ISSN |
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ISBN |
978-3-902613-06-6 |
Medium |
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Area |
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Expedition |
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Conference |
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Notes |
ADAS |
Approved |
no |
Call Number |
ADAS @ adas @ SGD2007 |
Serial |
797 |
Permanent link to this record |
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Author |
Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira |
Title |
Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives |
Type |
Journal Article |
Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
Volume |
83 |
Issue |
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Pages |
312-325 |
Keywords |
Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives |
Abstract |
When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques. |
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Publisher |
Elsevier B.V. |
Place of Publication |
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Conference |
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Notes |
ADAS; 600.086, 600.076 |
Approved |
no |
Call Number |
Admin @ si @OSS2016a |
Serial |
2806 |
Permanent link to this record |
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Author |
Angel Sappa; Cristhian A. Aguilera-Carrasco; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo |
Title |
Monocular visual odometry: A cross-spectral image fusion based approach |
Type |
Journal Article |
Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
Volume |
85 |
Issue |
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Pages |
26-36 |
Keywords |
Monocular visual odometry; LWIR-RGB cross-spectral imaging; Image fusion |
Abstract |
This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is empirically obtained by means of a mutual information based evaluation metric. The objective is to have a flexible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odometry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. |
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Publisher |
Elsevier B.V. |
Place of Publication |
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Edition |
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ISSN |
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Area |
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Expedition |
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Conference |
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Notes |
ADAS;600.086; 600.076 |
Approved |
no |
Call Number |
Admin @ si @SAC2016 |
Serial |
2811 |
Permanent link to this record |
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Author |
Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira |
Title |
Incremental texture mapping for autonomous driving |
Type |
Journal Article |
Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
Volume |
84 |
Issue |
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Pages |
113-128 |
Keywords |
Scene reconstruction; Autonomous driving; Texture mapping |
Abstract |
Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures. |
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Notes |
ADAS; 600.086 |
Approved |
no |
Call Number |
Admin @ si @ OSS2016b |
Serial |
2912 |
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Author |
David Aldavert; Ricardo Toledo |
Title |
Stereo Vision Local Map Alignment for Robot Environment Mapping |
Type |
Book Chapter |
Year |
2008 |
Publication |
Robot Vision Second International Workshop, RobVis |
Abbreviated Journal |
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Volume |
4931 |
Issue |
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Pages |
111–124 |
Keywords |
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Abstract |
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Address |
Auckland (New Zealand) |
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LNCS |
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Notes |
ADAS |
Approved |
no |
Call Number |
Admin @ si @ AlT2008 |
Serial |
1100 |
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Author |
O. Rodriguez; J. Mauri; E Fernandez-Nofrerias; C. Garcia; R. Villuendas; A. Tovar; A. Duran; V. Valle; Misael Rosales; Petia Radeva |
Title |
Model Empiric de Simulacio d Ecografia Intravascular |
Type |
Journal Article |
Year |
2003 |
Publication |
Revista Societat Catalana de Cardiologia, 4(4):42, XIVe Congres de la Societat Catalana de Cardiologia |
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Address |
Barcelona |
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Notes |
MILAB |
Approved |
no |
Call Number |
BCNPCL @ bcnpcl @ RMF2003e |
Serial |
412 |
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Author |
Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; M. Gomez; Antonio Tovar; L. Cano; C. Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva |
Title |
Ecografia Intracoronaria: Segmentacio Automatica de area de la llum |
Type |
Journal |
Year |
2002 |
Publication |
Revista Societat Catalana de Cardiologia |
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Volume |
4 |
Issue |
4 |
Pages |
42 |
Keywords |
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Abstract |
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Address |
Barcelona |
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XIVe Congres de la Societat Catalana de Cardiologia |
Notes |
MILAB;IAM |
Approved |
no |
Call Number |
BCNPCL @ bcnpcl @ RMF2002 |
Serial |
435 |
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Author |
J.L.Bruguera; R.Casado; M.Martinez; I.Corral; Enric Marti; L.A.Branda |
Title |
El apoyo institucional como elemento favorecedor de la coordinación docente: experiencias en diferentes universidades |
Type |
Miscellaneous |
Year |
2009 |
Publication |
Revista Red-U |
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Notes |
IAM |
Approved |
no |
Call Number |
IAM @ iam @ BCM2009 |
Serial |
1490 |
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Author |
Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva |
Title |
Utilización de la Estructura de los Campos Vectoriales para la Detección de la Adventicia en Imágenes de Ecografía Intracoronaria |
Type |
Journal Article |
Year |
2004 |
Publication |
Revista Internacional de Enfermedades Cardiovasculares Revista Española de Cardiología |
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Volume |
57 |
Issue |
2 |
Pages |
100 |
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Conference |
SEC |
Notes |
IAM;MILAB |
Approved |
no |
Call Number |
IAM @ iam @ RMF2004 |
Serial |
1642 |
Permanent link to this record |