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Author |
Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil |
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Title |
An illumination model of the trachea appearance in videobronchoscopy images |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Image Analysis and Recognition |
Abbreviated Journal |
LNCS |
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Volume |
7325 |
Issue |
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Pages |
313-320 |
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Keywords |
Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation |
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Abstract |
Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution. |
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Address |
Aveiro, Portugal |
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Publisher |
Springer Berlin Heidelberg |
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Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31297-7 |
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Area |
800 |
Expedition |
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Conference |
ICIAR |
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Notes |
MV;IAM |
Approved |
no |
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Call Number |
IAM @ iam @ SSR2012 |
Serial |
1898 |
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Permanent link to this record |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
Optimal Medial Surface Generation for Anatomical Volume Representations |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Abdominal Imaging. Computational and Clinical Applications |
Abbreviated Journal |
LNCS |
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Volume |
7601 |
Issue |
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Pages |
265-273 |
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Keywords |
Medial surface representation; volume reconstruction |
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Abstract |
Medial representations are a widely used technique in abdominal organ shape representation and parametrization. Those methods require good medial manifolds as a starting point. Any medial
surface used to parametrize a volume should be simple enough to allow an easy manipulation and complete enough to allow an accurate reconstruction of the volume. Obtaining good quality medial
surfaces is still a problem with current iterative thinning methods. This forces the usage of generic, pre-calculated medial templates that are adapted to the final shape at the cost of a drop in volume reconstruction.
This paper describes an operator for generation of medial structures that generates clean and complete manifolds well suited for their further use in medial representations of abdominal organ volumes. While being simpler than thinning surfaces, experiments show its high performance in volume reconstruction and preservation of medial surface main branching topology. |
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Address |
Nice, France |
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Publisher |
Springer Berlin Heidelberg |
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Editor |
Yoshida, Hiroyuki and Hawkes, David and Vannier, MichaelW. |
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Series Title |
Lecture Notes in Computer Science |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-33611-9 |
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Conference |
STACOM |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ VGG2012b |
Serial |
1988 |
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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 |
Abbreviated Journal |
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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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Publisher |
Springer Netherlands |
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Edition |
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ISSN |
0065-2598 |
ISBN |
978-94-007-7422-3 |
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Notes |
IAM; 600.075 |
Approved |
no |
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Call Number |
IAM @ iam @ RGG2014 |
Serial |
2197 |
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Permanent link to this record |
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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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Abbreviated Series Title |
LNCS |
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Conference |
CARE |
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Notes |
IAM; MV; 600.075 |
Approved |
no |
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Call Number |
Admin @ si @ GSF2015 |
Serial |
2733 |
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Permanent link to this record |
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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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Address |
Munich; Germany; January 2015 |
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Publisher |
Springer International Publishing |
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Abbreviated Series Title |
LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-319-28711-9 |
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Conference |
STACOM |
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Notes |
ADAS; IAM; 600.075; 600.076; 600.060; 601.145 |
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no |
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Call Number |
Admin @ si @ KHM2015 |
Serial |
2734 |
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Author |
H. Martin Kjer; 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 |
Abbreviated Journal |
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Volume |
11 |
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Notes |
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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Volume |
15 |
Issue |
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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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Notes |
IAM; DAG; 600.120; 600.145; 600.139 |
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Call Number |
Admin @ si @ GRP2021 |
Serial |
3594 |
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