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Author |
Debora Gil |
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Title |
Geometric Differential Operators for Shape Modelling |
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Book Whole |
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Year |
2004 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Medical imaging feeds research in many computer vision and image processing fields: image filtering, segmentation, shape recovery, registration, retrieval and pattern matching. Because of their low contrast changes and large variety of artifacts and noise, medical imaging processing techniques relying on an analysis of the geometry of image level sets rather than on intensity values result in more robust treatment. From the starting point of treatment of intravascular images, this PhD thesis ad- dresses the design of differential image operators based on geometric principles for a robust shape modelling and restoration. Among all fields applying shape recovery, we approach filtering and segmentation of image objects. For a successful use in real images, the segmentation process should go through three stages: noise removing, shape modelling and shape recovery. This PhD addresses all three topics, but for the sake of algorithms as automated as possible, techniques for image processing will be designed to satisfy three main principles: a) convergence of the iterative schemes to non-trivial states avoiding image degeneration to a constant image and representing smooth models of the originals; b) smooth asymptotic behav- ior ensuring stabilization of the iterative process; c) fixed parameter values ensuring equal (domain free) performance of the algorithms whatever initial images/shapes. Our geometric approach to the generic equations that model the different processes approached enables defining techniques satisfying all the former requirements. First, we introduce a new curvature-based geometric flow for image filtering achieving a good compromise between noise removing and resemblance to original images. Sec- ond, we describe a new family of diffusion operators that restrict their scope to image level curves and serve to restore smooth closed models from unconnected sets of points. Finally, we design a regularization of snake (distance) maps that ensures its smooth convergence towards any closed shape. Experiments show that performance of the techniques proposed overpasses that of state-of-the-art algorithms. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
Barcelona (Spain) |
Editor  |
Jordi Saludes i Closa;Petia Radeva |
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ISBN |
84-933652-0-3 |
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prit |
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Notes |
IAM; |
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no |
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Call Number |
IAM @ iam @ GIL2004 |
Serial |
1517 |
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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 Title |
Lecture Notes in Computer Science |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
3-540-40498-8 |
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Notes |
IAM;MILAB |
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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 |
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Book Chapter |
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Year |
2006 |
Publication |
Euro-Par 2006 Parallel Processing |
Abbreviated Journal |
LNCS |
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Volume |
4128 |
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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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IAM |
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Call Number |
IAM @ iam @ GRR2006a |
Serial |
1542 |
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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 |
Abbreviated Journal |
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Pages |
185-206 |
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Publisher |
Intech |
Place of Publication |
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Editor |
Yasuhiro Honda |
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Language |
English |
Summary Language |
english |
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ISBN |
978-953-307-900-4 |
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Notes |
IAM; ADAS |
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no |
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Call Number |
IAM @ iam @ HeG2012 |
Serial |
1684 |
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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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Lecture Notes in Computer Science |
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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 |
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Call Number |
IAM @ iam @ VGG2012b |
Serial |
1988 |
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