|
Records |
Links |
|
Author |
Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
|
|
Title |
Geometric Steerable Medial Maps |
Type |
Journal Article |
|
Year |
2013 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
|
|
Volume |
24 |
Issue |
6 |
Pages |
1255-1266 |
|
|
Keywords |
Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction |
|
|
Abstract |
In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological 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 avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
Mubarak Shah |
|
|
Language |
|
Summary Language ![sorted by Summary Language field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0932-8092 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; 605.203; 600.060; 600.044 |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VGB2013 |
Serial |
2192 |
|
Permanent link to this record |
|
|
|
|
Author |
Debora Gil; Sergio Vera; Agnes Borras; Albert Andaluz; Miguel Angel Gonzalez Ballester |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Anatomical Medial Surfaces with Efficient Resolution of Branches Singularities |
Type |
Journal Article |
|
Year |
2017 |
Publication |
Medical Image Analysis |
Abbreviated Journal |
MIA |
|
|
Volume |
35 |
Issue |
|
Pages |
390-402 |
|
|
Keywords |
Medial Representations; Shape Recognition; Medial Branching Stability ; Singular Points |
|
|
Abstract |
Medial surfaces are powerful tools for shape description, but their use has been limited due to the sensibility existing methods to branching artifacts. Medial branching artifacts are associated to perturbations of the object boundary rather than to geometric features. Such instability is a main obstacle for a condent application in shape recognition and description. Medial branches correspond to singularities of the medial surface and, thus, they are problematic for existing morphological and energy-based algorithms. In this paper, we use algebraic geometry concepts in an energy-based approach to compute a medial surface presenting a stable branching topology. We also present an ecient GPU-CPU implementation using standard image processing tools. We show the method computational eciency and quality on a custom made synthetic database. Finally, we present some results on a medical imaging application for localization of abdominal pathologies. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Elsevier B.V. |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language ![sorted by Summary Language field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; 600.060; 600.096; 600.075; 600.145 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GVB2017 |
Serial |
2775 |
|
Permanent link to this record |
|
|
|
|
Author |
H. Martin Kjer; Jens Fagertun; Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester; Rasmus R. Paulsena |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Free-form image registration of human cochlear uCT data using skeleton similarity as anatomical prior |
Type |
Journal Article |
|
Year |
2016 |
Publication |
Patter Recognition Letters |
Abbreviated Journal |
PRL |
|
|
Volume |
76 |
Issue |
1 |
Pages |
76-82 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language ![sorted by Summary Language field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; 600.060 |
Approved |
no |
|
|
Call Number |
Admin @ si @ MFV2017b |
Serial |
2941 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Multilocal Creaseness Measure |
Type |
Journal |
|
Year |
2012 |
Publication |
The Insight Journal |
Abbreviated Journal |
IJ |
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Ridges, Valley, Creaseness, Structure Tensor, Skeleton, |
|
|
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. |
|
|
Address |
|
|
|
Corporate Author |
Alma IT Systems |
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
english |
Summary Language ![sorted by Summary Language field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
english |
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM;ADAS; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VGL2012 |
Serial |
1840 |
|
Permanent link to this record |