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Author |
Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta |
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Title |
Robust and accurate diaphragm border detection in cardiac X-Ray angiographies |
Type |
Conference Article |
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Year |
2012 |
Publication |
Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges |
Abbreviated Journal |
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Volume |
7746 |
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Pages |
225-234 |
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Abstract |
Workshop STACOM, dins del MICCAI
X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods. |
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Nice, France |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-36960-5 |
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STACOM |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ PRC2012 |
Serial |
2028 |
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Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
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Title |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
Type |
Conference Article |
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Year |
2014 |
Publication |
17th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
8896 |
Issue |
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Pages |
231-238 |
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Keywords |
Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
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Abstract |
Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across dierent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three dierent OF methods, including HARP. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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ISSN |
0302-9743 |
ISBN |
978-3-319-14677-5 |
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STACOM |
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Notes |
IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
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no |
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Call Number |
Admin @ si @ MKF2014 |
Serial |
2495 |
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Author |
Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil |
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Title |
Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging |
Type |
Book Chapter |
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Year |
2015 |
Publication |
Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 |
Abbreviated Journal |
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Volume |
9534 |
Issue |
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Pages |
69-79 |
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Abstract |
Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm. |
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Munich; Germany; January 2015 |
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Springer International Publishing |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-319-28711-9 |
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STACOM |
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Notes |
ADAS; IAM; 600.075; 600.076; 600.060; 601.145 |
Approved |
no |
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Call Number |
Admin @ si @ KHM2015 |
Serial |
2734 |
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Author |
Antoni Gurgui; Debora Gil; Enric Marti; Vicente Grau |
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Title |
Left-Ventricle Basal Region Constrained Parametric Mapping to Unitary Domain |
Type |
Conference Article |
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Year |
2016 |
Publication |
7th International Workshop on Statistical Atlases & Computational Modelling of the Heart |
Abbreviated Journal |
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Volume |
10124 |
Issue |
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Pages |
163-171 |
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Keywords |
Laplacian; Constrained maps; Parameterization; Basal ring |
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Abstract |
Due to its complex geometry, the basal ring is often omitted when putting different heart geometries into correspondence. In this paper, we present the first results on a new mapping of the left ventricle basal rings onto a normalized coordinate system using a fold-over free approach to the solution to the Laplacian. To guarantee correspondences between different basal rings, we imposed some internal constrained positions at anatomical landmarks in the normalized coordinate system. To prevent internal fold-overs, constraints are handled by cutting the volume into regions defined by anatomical features and mapping each piece of the volume separately. Initial results presented in this paper indicate that our method is able to handle internal constrains without introducing fold-overs and thus guarantees one-to-one mappings between different basal ring geometries. |
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Athens; October 2016 |
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STACOM |
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Notes |
IAM; |
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no |
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Call Number |
Admin @ si @ GGM2016 |
Serial |
2884 |
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Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
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Title |
Improving Fuzzy Multilevel Graph Embedding through Feature Selection Technique |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
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Volume |
7626 |
Issue |
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Pages |
243-253 |
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Abstract |
Graphs are the most powerful, expressive and convenient data structures but there is a lack of efficient computational tools and algorithms for processing them. The embedding of graphs into numeric vector spaces permits them to access the state-of-the-art computational efficient statistical models and tools. In this paper we take forward our work on explicit graph embedding and present an improvement to our earlier proposed method, named “fuzzy multilevel graph embedding – FMGE”, through feature selection technique. FMGE achieves the embedding of attributed graphs into low dimensional vector spaces by performing a multilevel analysis of graphs and extracting a set of global, structural and elementary level features. Feature selection permits FMGE to select the subset of most discriminating features and to discard the confusing ones for underlying graph dataset. Experimental results for graph classification experimentation on IAM letter, GREC and fingerprint graph databases, show improvement in the performance of FMGE. |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-34165-6 |
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SSPR&SPR |
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DAG |
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no |
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Call Number |
Admin @ si @ LRL2012 |
Serial |
2381 |
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Permanent link to this record |
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Author |
Volkmar Frinken; Alicia Fornes; Josep Llados; Jean-Marc Ogier |
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Title |
Bidirectional Language Model for Handwriting Recognition |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
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Volume |
7626 |
Issue |
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Pages |
611-619 |
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Abstract |
In order to improve the results of automatically recognized handwritten text, information about the language is commonly included in the recognition process. A common approach is to represent a text line as a sequence. It is processed in one direction and the language information via n-grams is directly included in the decoding. This approach, however, only uses context on one side to estimate a word’s probability. Therefore, we propose a bidirectional recognition in this paper, using distinct forward and a backward language models. By combining decoding hypotheses from both directions, we achieve a significant increase in recognition accuracy for the off-line writer independent handwriting recognition task. Both language models are of the same type and can be estimated on the same corpus. Hence, the increase in recognition accuracy comes without any additional need for training data or language modeling complexity. |
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Japan |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-34165-6 |
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SSPR&SPR |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ FFL2012 |
Serial |
2057 |
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Permanent link to this record |
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Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
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Title |
Hierarchical graph representation for symbol spotting in graphical document images |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
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Volume |
7626 |
Issue |
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Pages |
529-538 |
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Abstract |
Symbol spotting can be defined as locating given query symbol in a large collection of graphical documents. In this paper we present a hierarchical graph representation for symbols. This representation allows graph matching methods to deal with low-level vectorization errors and, thus, to perform a robust symbol spotting. To show the potential of this approach, we conduct an experiment with the SESYD dataset. |
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Address |
Miyajima-Itsukushima, Hiroshima |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-34165-6 |
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SSPR&SPR |
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DAG |
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no |
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Call Number |
Admin @ si @ BDJ2012 |
Serial |
2126 |
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Permanent link to this record |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke; Alicia Fornes |
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Title |
On the Correlation of Graph Edit Distance and L1 Distance in the Attribute Statistics Embedding Space |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
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Volume |
7626 |
Issue |
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135-143 |
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Graph embeddings in vector spaces aim at assigning a pattern vector to every graph so that the problems of graph classification and clustering can be solved by using data processing algorithms originally developed for statistical feature vectors. An important requirement graph features should fulfil is that they reproduce as much as possible the properties among objects in the graph domain. In particular, it is usually desired that distances between pairs of graphs in the graph domain closely resemble those between their corresponding vectorial representations. In this work, we analyse relations between the edit distance in the graph domain and the L1 distance of the attribute statistics based embedding, for which good classification performance has been reported on various datasets. We show that there is actually a high correlation between the two kinds of distances provided that the corresponding parameter values that account for balancing the weight between node and edge based features are properly selected. |
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Springer-Berlag, Berlin |
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978-3-642-34165-6 |
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SSPR&SPR |
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DAG |
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no |
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Call Number |
Admin @ si @ GVB2012c |
Serial |
2167 |
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Permanent link to this record |
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Author |
Fadi Dornaika; A.Assoum; Bogdan Raducanu |
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Title |
Automatic Dimensionality Estimation for Manifold Learning through Optimal Feature Selection |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
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Volume |
7626 |
Issue |
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Pages |
575-583 |
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A very important aspect in manifold learning is represented by automatic estimation of the intrinsic dimensionality. Unfortunately, this problem has received few attention in the literature of manifold learning. In this paper, we argue that feature selection paradigm can be used to the problem of automatic dimensionality estimation. Besides this, it also leads to improved recognition rates. Our approach for optimal feature selection is based on a Genetic Algorithm. As a case study for manifold learning, we have considered Laplacian Eigenmaps (LE) and Locally Linear Embedding (LLE). The effectiveness of the proposed framework was tested on the face recognition problem. Extensive experiments carried out on ORL, UMIST, Yale, and Extended Yale face data sets confirmed our hypothesis. |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-34165-6 |
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SSPR&SPR |
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Notes |
OR;MV |
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no |
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Call Number |
Admin @ si @ DAR2012 |
Serial |
2174 |
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Permanent link to this record |
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Author |
Bogdan Raducanu; Fadi Dornaika |
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Title |
Out-of-Sample Embedding by Sparse Representation |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
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Volume |
7626 |
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336-344 |
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A critical aspect of non-linear dimensionality reduction techniques is represented by the construction of the adjacency graph. The difficulty resides in finding the optimal parameters, a process which, in general, is heuristically driven. Recently, sparse representation has been proposed as a non-parametric solution to overcome this problem. In this paper, we demonstrate that this approach not only serves for the graph construction, but also represents an efficient and accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. Experimental results conducted on some challenging datasets confirmed the robustness of our approach and its superiority when compared to existing techniques. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-34165-6 |
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SSPR&SPR |
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OR;MV |
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no |
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Call Number |
Admin @ si @ RaD2012c |
Serial |
2175 |
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Permanent link to this record |
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Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa; Horst Bunke |
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Title |
Exact Median Graph Computation via Graph Embedding |
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Conference Article |
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2008 |
Publication |
12th International Workshop on Structural and Syntactic Pattern Recognition |
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5324 |
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15–24 |
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Orlando – Florida (USA) |
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DAG |
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no |
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DAG @ dag @ FVS2008b |
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1076 |
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Permanent link to this record |
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Author |
Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester |
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Title |
Anatomical parameterization for volumetric meshing of the liver |
Type |
Conference Article |
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Year |
2014 |
Publication |
SPIE – Medical Imaging |
Abbreviated Journal |
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Volume |
9036 |
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Coordinate System; Anatomy Modeling; Parameterization |
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Abstract |
A coordinate system describing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specific anatomical landmarks, the coordinate system allows integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric coordinate systems over the surface of anatomical shapes, given their flexibility to set values
at specific locations through boundary conditions. However, most of the existing implementations in medical imaging restrict to either anatomical surfaces, or the depth coordinate with boundary conditions is given at sites
of limited geometric diversity. In this paper we present a method for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the
volume medial surface. We have applied the methodology to define a common reference system for the liver shape and functional anatomy. This reference system sets a solid base for creating anatomical models of the patient’s liver, and allows comparing livers from several patients in a common framework of reference. |
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Amsterdam; September 2014 |
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SPIE-MI |
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Notes |
IAM; 600.075 |
Approved |
no |
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Call Number |
Admin @ si @ VGG2014 |
Serial |
2456 |
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Permanent link to this record |
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Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
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Title |
Fast Structural Matching for Document Image Retrieval through Spatial Databases |
Type |
Conference Article |
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Year |
2014 |
Publication |
Document Recognition and Retrieval XXI |
Abbreviated Journal |
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Volume |
9021 |
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Keywords |
Document image retrieval; distance transform; MSER; spatial database |
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Abstract |
The structure of document images plays a signicant role in document analysis thus considerable eorts have been made towards extracting and understanding document structure, usually in the form of layout analysis approaches. In this paper, we rst employ Distance Transform based MSER (DTMSER) to eciently extract stable document structural elements in terms of a dendrogram of key-regions. Then a fast structural matching method is proposed to query the structure of document (dendrogram) based on a spatial database which facilitates the formulation of advanced spatial queries. The experiments demonstrate a signicant improvement in a document retrieval scenario when compared to the use of typical Bag of Words (BoW) and pyramidal BoW descriptors. |
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Amsterdam; September 2014 |
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DAG; 600.056; 600.061; 600.077 |
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Admin @ si @ GRK2014a |
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2496 |
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Debora Gil; Jaume Garcia; Aura Hernandez-Sabate; Enric Marti |
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Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy |
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2010 |
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8th Medical Imaging |
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7623 |
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762304 |
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304 |
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Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature. |
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IAM |
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IAM @ iam @ GGH2010a |
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1522 |
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Author |
Vishwesh Pillai; Pranav Mehar; Manisha Das; Deep Gupta; Petia Radeva |
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Integrated Hierarchical and Flat Classifiers for Food Image Classification using Epistemic Uncertainty |
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2022 |
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IEEE International Conference on Signal Processing and Communications |
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The problem of food image recognition is an essential one in today’s context because health conditions such as diabetes, obesity, and heart disease require constant monitoring of a person’s diet. To automate this process, several models are available to recognize food images. Due to a considerable number of unique food dishes and various cuisines, a traditional flat classifier ceases to perform well. To address this issue, prediction schemes consisting of both flat and hierarchical classifiers, with the analysis of epistemic uncertainty are used to switch between the classifiers. However, the accuracy of the predictions made using epistemic uncertainty data remains considerably low. Therefore, this paper presents a prediction scheme using three different threshold criteria that helps to increase the accuracy of epistemic uncertainty predictions. The performance of the proposed method is demonstrated using several experiments performed on the MAFood-121 dataset. The experimental results validate the proposal performance and show that the proposed threshold criteria help to increase the overall accuracy of the predictions by correctly classifying the uncertainty distribution of the samples. |
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Bangalore; India; July 2022 |
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SPCOM |
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MILAB; no menciona |
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Admin @ si @ PMD2022 |
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3796 |
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