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Sergio Vera. (2010). "Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis " (Vol. 164). Master's thesis, , Bellaterra 01893, Barcelona, Spain.
Abstract: Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research.
Keywords: Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score
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Sergio Vera, Debora Gil, Antonio Lopez, & Miguel Angel Gonzalez Ballester. (2012). "Multilocal Creaseness Measure " . The Insight Journal, .
Abstract: This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission.
Keywords: Ridges, Valley, Creaseness, Structure Tensor, Skeleton,
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Sergio Vera, Miguel Angel Gonzalez Ballester, & Debora Gil. (2013). "Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition " In 16th International Conference on Medical Image Computing and Computer Assisted Intervention.
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Sergio Vera, Debora Gil, & Miguel Angel Gonzalez Ballester. (2014). "Anatomical parameterization for volumetric meshing of the liver " In SPIE – Medical Imaging (Vol. 9036).
Abstract: A coordinate system describing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specific anatomical landmarks, the coordinate system allows integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric coordinate systems over the surface of anatomical shapes, given their flexibility to set values
at specific 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 sites
of limited geometric diversity. In this paper we present a method for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the
volume medial surface. We have applied the methodology to define a common reference system for the liver shape and functional anatomy. This reference system sets a solid base for creating anatomical models of the patient’s liver, and allows comparing livers from several patients in a common framework of reference.
Keywords: Coordinate System; Anatomy Modeling; Parameterization
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Sergio Vera. (2015)." Anatomic Registration based on Medial Axis Parametrizations" (Debora Gil, & Miguel Angel Gonzalez Ballester, Eds.). Ph.D. thesis, Ediciones Graficas Rey, .
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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H. Martin Kjer, Jens Fagertun, Sergio Vera, & Debora Gil. (2017). "Medial structure generation for registration of anatomical structures " In Skeletonization, Theory, Methods and Applications (Vol. 11).
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Sergio Vera, Miguel Angel Gonzalez Ballester, & Debora Gil. (2015). "A Novel Cochlear Reference Frame Based On The Laplace Equation " In 29th international Congress and Exhibition on Computer Assisted Radiology and Surgery (Vol. 10, pp. 1–312).
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H. Martin Kjer, Jens Fagertun, Sergio Vera, Debora Gil, Miguel Angel Gonzalez Ballester, & Rasmus R. Paulsena. (2016). "Free-form image registration of human cochlear uCT data using skeleton similarity as anatomical prior " . Patter Recognition Letters, 76(1), 76–82.
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Sergio Vera, Debora Gil, Agnes Borras, F. Javier Sanchez, Frederic Perez, Marius G. Linguraru, et al. (2012). "Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs " In H. Yoshida et al (Ed.), Workshop on Computational and Clinical Applications in Abdominal Imaging (Vol. 7029, 223–230). Lecture Notes in Computer Science. Berlin: Springer Link.
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.
Keywords: medial manifolds, abdomen.
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Sergio Vera, Debora Gil, Agnes Borras, F. Javier Sanchez, Frederic Perez, & Marius G. Linguraru. (2011)." Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs" In In H. Yoshida et al (Ed.), Workshop on Computational and Clinical Applications in Abdominal Imaging (Vol. 7029, pp. 223–230). Springer Berlin Heidelberg.
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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