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Author |
Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil |
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Title |
Suppression of IVUS Image Rotation. A Kinematic Approach |
Type |
Book Chapter |
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Year |
2005 |
Publication |
Functional Imaging and Modeling of the Heart |
Abbreviated Journal |
LNCS |
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Volume |
3504 |
Issue |
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Pages |
889-892 |
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Abstract |
IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology. |
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Springer Berlin / Heidelberg |
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Editor |
Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica |
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Series Title |
Lecture Notes in Computer Science |
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LNCS |
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Series Volume |
3504 |
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IAM;MILAB |
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Call Number |
IAM @ iam @ RRR2005 |
Serial |
1645 |
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Author |
Fernando Vilariño; Debora Gil; Petia Radeva |
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Title |
A Novel FLDA Formulation for Numerical Stability Analysis |
Type |
Book Chapter |
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Year |
2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
Abbreviated Journal |
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Volume |
113 |
Issue |
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Pages |
77-84 |
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Keywords |
Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision |
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Abstract |
Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision. |
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IOS Press |
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Editor |
J. Vitrià, P. Radeva and I. Aguiló |
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978-1-58603-466-5 |
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Notes |
MV;IAM;MILAB;SIAI |
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Call Number |
IAM @ iam @ VGR2004 |
Serial |
1663 |
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Author |
Aura Hernandez-Sabate; Debora Gil |
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Title |
The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Intravascular Ultrasound |
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Pages |
185-206 |
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Intech |
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Editor |
Yasuhiro Honda |
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Language |
English |
Summary Language |
english |
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978-953-307-900-4 |
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IAM; ADAS |
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Call Number |
IAM @ iam @ HeG2012 |
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1684 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? |
Type |
Book Chapter |
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Year |
2014 |
Publication |
G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology |
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Volume |
796 |
Issue |
3 |
Pages |
159-181 |
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Keywords |
β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model |
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Abstract |
Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists. |
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Springer Netherlands |
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ISSN |
0065-2598 |
ISBN |
978-94-007-7422-3 |
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Notes |
IAM; 600.075 |
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Call Number |
IAM @ iam @ RGG2014 |
Serial |
2197 |
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Author |
Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal |
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Title |
3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos |
Type |
Book Chapter |
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Year |
2015 |
Publication |
Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 |
Abbreviated Journal |
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Volume |
9515 |
Issue |
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Pages |
140-152 |
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Keywords |
Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds |
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Abstract |
Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection. |
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LNCS |
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CARE |
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Notes |
IAM; MV; 600.075 |
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Call Number |
Admin @ si @ GSF2015 |
Serial |
2733 |
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Author |
H. Martin ; Jens Fagertun; Sergio Vera; Debora Gil |
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Title |
Medial structure generation for registration of anatomical structures |
Type |
Book Chapter |
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Year |
2017 |
Publication |
Skeletonization, Theory, Methods and Applications |
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11 |
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IAM; 600.096; 600.075; 600.145 |
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Call Number |
Admin @ si @ MFV2017a |
Serial |
2935 |
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Author |
Debora Gil; Oriol Ramos Terrades; Raquel Perez |
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Title |
Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution |
Type |
Book Chapter |
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Year |
2021 |
Publication |
Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 |
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15 |
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Pages |
89–93 |
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Abstract |
Abnormalities in radiomic measures correlate to genomic alterations prone to alter the outcome of personalized anti-cancer treatments. TOPiomics is a new method for the early detection of variations in tumor imaging phenotype from a topological structure in multi-view radiomic spaces. |
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Springer Nature |
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IAM; DAG; 600.120; 600.145; 600.139 |
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Admin @ si @ GRP2021 |
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3594 |
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