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Author |
Antonio Esteban Lansaque |

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Title |
An Endoscopic Navigation System for Lung Cancer Biopsy |
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Book Whole |
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Year |
2019 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
Lung cancer is one of the most diagnosed cancers among men and women. Actually,
lung cancer accounts for 13% of the total cases with a 5-year global survival
rate in patients. Although Early detection increases survival rate from 38% to 67%, accurate diagnosis remains a challenge. Pathological confirmation requires extracting a sample of the lesion tissue for its biopsy. The preferred procedure for tissue biopsy is called bronchoscopy. A bronchoscopy is an endoscopic technique for the internal exploration of airways which facilitates the performance of minimal invasive interventions with low risk for the patient. Recent advances in bronchoscopic devices have increased their use for minimal invasive diagnostic and intervention procedures, like lung cancer biopsy sampling. Despite the improvement in bronchoscopic device quality, there is a lack of intelligent computational systems for supporting in-vivo clinical decision during examinations. Existing technologies fail to accurately reach the lesion due to several aspects at intervention off-line planning and poor intra-operative guidance at exploration time. Existing guiding systems radiate patients and clinical staff,might be expensive and achieve a suboptimlal 70% of yield boost. Diagnostic yield could be improved reducing radiation and costs by developing intra-operative support systems able to guide the bronchoscopist to the lesion during the intervention. The goal of this PhD thesis is to develop an image-based navigation systemfor intra-operative guidance of bronchoscopists to a target lesion across a path previously planned on a CT-scan. We propose a 3D navigation system which uses the anatomy of video bronchoscopy frames to locate the bronchoscope within the airways. Once the bronchoscope is located, our navigation system is able to indicate the bifurcation which needs to be followed to reach the lesion. In order to facilitate an off-line validation
as realistic as possible, we also present a method for augmenting simulated virtual bronchoscopies with the appearance of intra-operative videos. Experiments performed on augmented and intra-operative videos, prove that our algorithm can be speeded up for an on-line implementation in the operating room. |
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October 2019 |
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Corporate Author |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor  |
Debora Gil; Carles Sanchez |
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ISBN |
978-84-121011-0-2 |
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Notes |
IAM; 600.139; 600.145 |
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no |
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Call Number |
Admin @ si @ Est2019 |
Serial |
3392 |
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Author |
David Roche |

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Title |
A Statistical Framework for Terminating Evolutionary Algorithms at their Steady State |
Type |
Book Whole |
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Year |
2015 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
As any iterative technique, it is a necessary condition a stop criterion for terminating Evolutionary Algorithms (EA). In the case of optimization methods, the algorithm should stop at the time it has reached a steady state so it can not improve results anymore. Assessing the reliability of termination conditions for EAs is of prime importance. A wrong or weak stop criterion can negatively aect both the computational eort and the nal result.
In this Thesis, we introduce a statistical framework for assessing whether a termination condition is able to stop EA at its steady state. In one hand a numeric approximation to steady states to detect the point in which EA population has lost its diversity has been presented for EA termination. This approximation has been applied to dierent EA paradigms based on diversity and a selection of functions covering the properties most relevant for EA convergence. Experiments show that our condition works regardless of the search space dimension and function landscape and Dierential Evolution (DE) arises as the best paradigm. On the other hand, we use a regression model in order to determine the requirements ensuring that a measure derived from EA evolving population is related to the distance to the optimum in xspace.
Our theoretical framework is analyzed across several benchmark test functions
and two standard termination criteria based on function improvement in f-space and EA population x-space distribution for the DE paradigm. Results validate our statistical framework as a powerful tool for determining the capability of a measure for terminating EA and select the x-space distribution as the best-suited for accurately stopping DE in real-world applications. |
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Address |
July 2015 |
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Corporate Author |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor  |
Debora Gil; Jesus Giraldo |
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Notes |
IAM; 600.075 |
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no |
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Call Number |
Admin @ si @ Roc2015 |
Serial |
2686 |
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Author |
Debora Gil; Jordi Gonzalez; Gemma Sanchez (eds) |

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Title |
Computer Vision: Advances in Research and Development |
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Book Whole |
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Year |
2007 |
Publication |
Proceedings of the 2nd CVC International Workshop |
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Publisher |
UAB |
Place of Publication |
Bellaterra (Spain) |
Editor  |
Debora Gil; Jordi Gonzalez; Gemma Sanchez |
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2 |
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ISBN |
978-84-935251-4-9 |
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Notes |
IAM; ISE; DAG |
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no |
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Call Number |
IAM @ iam @ GGS2007 |
Serial |
1493 |
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Author |
Sergio Vera |

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Title |
Anatomic Registration based on Medial Axis Parametrizations |
Type |
Book Whole |
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Year |
2015 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
Image registration has been for many years the gold standard method to bring two images into correspondence. It has been used extensively in the eld of medical imaging in order to put images of dierent patients into a common overlapping spatial position. However, medical image registration is a slow, iterative optimization process, where many variables and prone to fall into the pit traps local minima.
A coordinate system parameterizing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specic anatomical sites, parameterizations ensure integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric meshes over the surface of anatomical shapes, given their ability to set values at specic 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 discrete sites of limited geometric diversity.
The medial surface of the shape can be used to provide a continuous basis for the denition of a depth coordinate. However, given that dierent methods for generation of medial surfaces generate dierent manifolds, not all of them are equally suited to be the basis of radial coordinate for a parameterization. It would be desirable that the medial surface will be smooth, and robust to surface shape noise, with low number of spurious branches or surfaces.
In this thesis we present methods for computation of smooth medial manifolds and apply them to the generation of for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the volume medial surface. This reference system sets a solid base for creating anatomical models of the anatomical shapes, and allows comparing several patients in a common framework of reference. |
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Address |
November 2015 |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor  |
Debora Gil; Miguel Angel Gonzalez Ballester |
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ISBN |
978-84-943427-8-3 |
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Notes |
IAM; 600.075 |
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no |
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Call Number |
Admin @ si @ Ver2015 |
Serial |
2708 |
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Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |



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Title |
Symbol recognition: current advances and perspectives |
Type |
Book Chapter |
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Year |
2002 |
Publication |
Graphics Recognition Algorithms And Applications |
Abbreviated Journal |
LNCS |
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Volume |
2390 |
Issue |
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Pages |
104-128 |
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Abstract |
The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
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Address |
London, UK |
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Publisher |
Springer-Verlag |
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Editor  |
Dorothea Blostein and Young- Bin Kwon |
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Series Title |
Lecture Notes in Computer Science |
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LNCS |
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ISBN |
3-540-44066-6 |
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Conference |
GREC |
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Notes |
DAG; IAM; |
Approved |
no |
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Call Number |
IAM @ iam @ LVS2002 |
Serial |
1572 |
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Permanent link to this record |
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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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Publisher |
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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Edition |
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Conference |
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Notes |
IAM;MILAB |
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no |
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Call Number |
IAM @ iam @ RRR2005 |
Serial |
1645 |
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Permanent link to this record |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester |


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Title |
Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Workshop on Computational and Clinical Applications in Abdominal Imaging |
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Volume |
7029 |
Issue |
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Pages |
223–230 |
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Keywords |
medial manifolds, abdomen. |
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Abstract |
Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations. |
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Address |
Toronto; Canada; |
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Publisher |
Springer Link |
Place of Publication |
Berlin |
Editor  |
H. Yoshida et al |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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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 |
978-3-642-28556-1 |
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Conference |
ABDI |
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Notes |
IAM;MV |
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no |
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Call Number |
IAM @ iam @ VGB2012 |
Serial |
1834 |
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Permanent link to this record |
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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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Publisher |
IOS Press |
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Editor  |
J. Vitrià, P. Radeva and I. Aguiló |
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ISBN |
978-1-58603-466-5 |
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Notes |
MV;IAM;MILAB |
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no |
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Call Number |
IAM @ iam @ VGR2004 |
Serial |
1663 |
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Permanent link to this record |
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Author |
Debora Gil; Petia Radeva |



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Title |
Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling |
Type |
Book Chapter |
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Year |
2003 |
Publication |
Energy Minimization Methods In Computer Vision And Pattern Recognition |
Abbreviated Journal |
LNCS |
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Volume |
2683 |
Issue |
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Pages |
357-372 |
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Keywords |
Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature |
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Abstract |
Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time. |
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Publisher |
Springer, Berlin |
Place of Publication |
Lisbon, PORTUGAL |
Editor  |
Springer, B. |
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Series Editor |
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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 |
3-540-40498-8 |
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Notes |
IAM;MILAB |
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no |
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Call Number |
IAM @ iam @ GIR2003b |
Serial |
1535 |
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Author |
F.Guirado; Ana Ripoll; C.Roig; Aura Hernandez-Sabate; Emilio Luque |

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Title |
Exploiting Throughput for Pipeline Execution in Streaming Image Processing Applications |
Type |
Book Chapter |
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Year |
2006 |
Publication |
Euro-Par 2006 Parallel Processing |
Abbreviated Journal |
LNCS |
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Volume |
4128 |
Issue |
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Pages |
1095-1105 |
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Keywords |
12th International Euro–Par Conference |
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Abstract |
There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when execu- ting them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodo- logy we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate. |
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Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
Dresden, Germany (European Union) |
Editor  |
UAB; W, E.N.; et al. |
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Lecture Notes In Computer Science |
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Euro–Par |
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Notes |
IAM |
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no |
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Call Number |
IAM @ iam @ GRR2006a |
Serial |
1542 |
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