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Author |
Sergio Vera |
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Title |
Anatomic Registration based on Medial Axis Parametrizations |
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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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November 2015 |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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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 |
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 |
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2197 |
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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 |
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Book Chapter |
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Year |
2012 |
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Intravascular Ultrasound |
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Pages |
185-206 |
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Publisher |
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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Notes |
IAM; ADAS |
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Call Number |
IAM @ iam @ HeG2012 |
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1684 |
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Author |
Enric Marti; Jordi Regincos; Juan Jose Villanueva; Jaime Lopez-Krahe |
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Title |
Line drawing interpretation as polyhedral objects to man-machine interaction in CAD systems |
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Book Chapter |
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Year |
1994 |
Publication |
Advances in Pattern Recognition and Image Analysis, |
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158-169 |
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World Scientific Pub. |
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ISBN |
981-02-1872-9 |
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Notes |
IAM;ISE |
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no |
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Call Number |
IAM @ iam @ MRL1994 |
Serial |
1609 |
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