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Records |
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Author |
Marina Alberti |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Detection and Alignment of Vascular Structures in Intravascular Ultrasound using Pattern Recognition Techniques |
Type |
Book Whole |
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Year |
2013 |
Publication |
PhD Thesis, Universitat de Barcelona-CVC |
Abbreviated Journal |
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Abstract |
In this thesis, several methods for the automatic analysis of Intravascular Ultrasound
(IVUS) sequences are presented, aimed at assisting physicians in the diagnosis, the assessment of the intervention and the monitoring of the patients with coronary disease.
The basis for the developed frameworks are machine learning, pattern recognition and
image processing techniques.
First, a novel approach for the automatic detection of vascular bifurcations in
IVUS is presented. The task is addressed as a binary classication problem (identifying bifurcation and non-bifurcation angular sectors in the sequence images). The
multiscale stacked sequential learning algorithm is applied, to take into account the
spatial and temporal context in IVUS sequences, and the results are rened using
a-priori information about branching dimensions and geometry. The achieved performance is comparable to intra- and inter-observer variability.
Then, we propose a novel method for the automatic non-rigid alignment of IVUS
sequences of the same patient, acquired at dierent moments (before and after percutaneous coronary intervention, or at baseline and follow-up examinations). The
method is based on the description of the morphological content of the vessel, obtained by extracting temporal morphological proles from the IVUS acquisitions, by
means of methods for segmentation, characterization and detection in IVUS. A technique for non-rigid sequence alignment – the Dynamic Time Warping algorithm -
is applied to the proles and adapted to the specic clinical problem. Two dierent robust strategies are proposed to address the partial overlapping between frames
of corresponding sequences, and a regularization term is introduced to compensate
for possible errors in the prole extraction. The benets of the proposed strategy
are demonstrated by extensive validation on synthetic and in-vivo data. The results
show the interest of the proposed non-linear alignment and the clinical value of the
method.
Finally, a novel automatic approach for the extraction of the luminal border in
IVUS images is presented. The method applies the multiscale stacked sequential
learning algorithm and extends it to 2-D+T, in a rst classication phase (the identi-
cation of lumen and non-lumen regions of the images), while an active contour model
is used in a second phase, to identify the lumen contour. The method is extended
to the longitudinal dimension of the sequences and it is validated on a challenging
data-set. |
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Address |
Barcelona |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Simone Balocco;Petia Radeva |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ Alb2013 |
Serial |
2215 |
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Author |
Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Estado del Arte en Sistemas de Vision Artificial para Personas Invidentes |
Type |
Journal |
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Year |
2013 |
Publication |
Komputer Sapiens |
Abbreviated Journal |
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Volume |
1 |
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Pages |
20-25 |
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OR;MV |
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no |
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Call Number |
Admin @ si @ TSR2013 |
Serial |
2231 |
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Author |
Sergio Escalera |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Coding and Decoding Design of ECOCs for Multi-class Pattern and Object Recognition A |
Type |
Book Whole |
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Year |
2008 |
Publication |
PhD Thesis, Universitat de Barcelona-CVC |
Abbreviated Journal |
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Many real problems require multi-class decisions. In the Pattern Recognition field,
many techniques have been proposed to deal with the binary problem. However,
the extension of many 2-class classifiers to the multi-class case is a hard task. In
this sense, Error-Correcting Output Codes (ECOC) demonstrated to be a powerful
tool to combine any number of binary classifiers to model multi-class problems. But
there are still many open issues about the capabilities of the ECOC framework. In
this thesis, the two main stages of an ECOC design are analyzed: the coding and
the decoding steps. We present different problem-dependent designs. These designs
take advantage of the knowledge of the problem domain to minimize the number
of classifiers, obtaining a high classification performance. On the other hand, we
analyze the ECOC codification in order to define new decoding rules that take full
benefit from the information provided at the coding step. Moreover, as a successful
classification requires a rich feature set, new feature detection/extraction techniques
are presented and evaluated on the new ECOC designs. The evaluation of the new
methodology is performed on different real and synthetic data sets: UCI Machine
Learning Repository, handwriting symbols, traffic signs from a Mobile Mapping System, Intravascular Ultrasound images, Caltech Repository data set or Chaga’s disease
data set. The results of this thesis show that significant performance improvements
are obtained on both traditional coding and decoding ECOC designs when the new
coding and decoding rules are taken into account. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Petia Radeva;Oriol Pujol |
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MILAB; HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ Esc2008b |
Serial |
2217 |
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Author |
David Augusto Rojas |
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Title |
Colouring Local Feature Detection for Matching |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
133 |
Issue |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Roj2009 |
Serial |
2392 |
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Permanent link to this record |
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Author |
Juan Diego Gomez |
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Title |
Toward Robust Myocardial Blush Grade Estimation in Contrast Angiography |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
134 |
Issue |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ Gom2009 |
Serial |
2393 |
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Permanent link to this record |
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Author |
Olivier Penacchio |
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Title |
Relative Density of L, M, S photoreceptors in the Human Retina |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
135 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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Notes |
CIC |
Approved |
no |
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Call Number |
Admin @ si @ Pen2009 |
Serial |
2394 |
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Permanent link to this record |
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Author |
Xavier Boix |
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Title |
Learning Conditional Random Fields for Stereo |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
136 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Boi2009 |
Serial |
2395 |
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Permanent link to this record |
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Author |
Shida Beigpour |
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Title |
Physics-based Reflectance Estimation Applied to Recoloring |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
137 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
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no |
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Call Number |
Admin @ si @ Bei2009 |
Serial |
2396 |
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Author |
Jaume Gibert |
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Title |
Learning structural representations and graph matching paradigms in the context of object recognition |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
143 |
Issue |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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DAG |
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no |
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Call Number |
Admin @ si @ Gib2009 |
Serial |
2397 |
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Author |
Jose Carlos Rubio |
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Title |
Graph matching based on graphical models with application to vehicle tracking and classification at night |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
144 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Rub2009 |
Serial |
2398 |
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Author |
Farshad Nourbakhsh |
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Title |
Colour logo recognition |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
145 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ Nou2009 |
Serial |
2399 |
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Permanent link to this record |
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Author |
Enric Sala |
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Title |
Off-line person-dependent signature verification |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
146 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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no |
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Call Number |
Admin @ si @ Sal2009 |
Serial |
2400 |
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Permanent link to this record |
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Author |
Wenjuan Gong |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Action priors for human pose tracking by particle filter |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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ISE |
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Admin @ si @ Gon2009 |
Serial |
2401 |
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Author |
Diego Alejandro Cheda |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Monocular egomotion estimation for ADAS application |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
148 |
Issue |
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Corporate Author |
Computer Vision Center |
Thesis |
Ph.D. thesis |
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Place of Publication |
Bellaterra, Barcelona |
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ADAS |
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Call Number |
Admin @ si @ Che2009 |
Serial |
2402 |
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Author |
Javier Marin |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Virtual learning for real testing |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
150 |
Issue |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
bell |
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ADAS |
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no |
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Call Number |
Admin @ si @ Mar2009c |
Serial |
2403 |
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Permanent link to this record |