toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
  Records Links
Author Joan M. Nuñez edit   pdf
openurl 
  Title (up) Computer vision techniques for characterization of finger joints in X-ray image Type Report
  Year 2011 Publication CVC Technical Report Abbreviated Journal  
  Volume 165 Issue Pages  
  Keywords Rheumatoid arthritis, X-ray, Sharp Van der Heijde, joint characterization, sclerosis detection, bone detection, edge, ridge  
  Abstract Rheumatoid arthritis (RA) is an autoimmune inflammatory type of arthritis which mainly affects hands on its first stages. Though it is a chronic disease and there is no cure for it, treatments require an accurate assessment of illness evolution. Such assessment is based on evaluation of hand X-ray images by using one of the several available semi-quantitative methods. This task requires highly trained medical personnel. That is why the automation of the assessment would allow professionals to save time and effort. Two stages are involved in this task. Firstly, the joint detection, afterwards, the joint characterization. Unlike the little existing previous work, this contribution clearly separates those two stages and sets the foundations of a modular assessment system focusing on the characterization stage. A hand joint dataset is created and an accurate data analysis is achieved in order to identify relevant features. Since the sclerosis and the lower bone were decided to be the most important features, different computer vision techniques were used in order to develop a detector system for both of them. Joint space width measures are provided and their correlation with Sharp-Van der Heijde is verified  
  Address Bellaterra (Barcelona)  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Editor Dr. Fernando Vilariño and Dra. Debora Gil  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MV;IAM; Approved no  
  Call Number IAM @ iam @ Nuñ2011 Serial 1795  
Permanent link to this record
 

 
Author Debora Gil; Jordi Gonzalez; Gemma Sanchez (eds) edit  isbn
openurl 
  Title (up) Computer Vision: Advances in Research and Development Type Book Whole
  Year 2007 Publication Proceedings of the 2nd CVC International Workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher UAB Place of Publication Bellaterra (Spain) Editor Debora Gil; Jordi Gonzalez; Gemma Sanchez  
  Language Summary Language Original Title  
  Series Editor Series Title 2 Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-935251-4-9 Medium  
  Area Expedition Conference  
  Notes IAM; ISE; DAG Approved no  
  Call Number IAM @ iam @ GGS2007 Serial 1493  
Permanent link to this record
 

 
Author Patricia Marquez edit   pdf
openurl 
  Title (up) Conditions Ensuring Accuracy of Local Optical Flow Schemes Type Report
  Year 2010 Publication CVC Tehcnical Report Abbreviated Journal  
  Volume 157 Issue Pages  
  Keywords  
  Abstract Accurate computation of optical flow is a key-point in many image processing fields. Detection of anomalous and unpredicted agents (such as pedestrians, bikers or cars) in urban scenes or pathology discrimination in medical imaging sequences, to mention just a two. The above kinds sequences present two main difficulties for standard optical flow techniques. On one hand, variability in acquisition conditions (illuminance, medical imaging modality, ...) force an alterantive representation for images fulfilling the britghtness constancy constrain. On the hand, current variational schemes produce oversmoothed fields unable to properly model discontinuous behaviours such as collisions or functionless pathological areas. This master project explores the abilities and limitations of local and global optical flow approaches. The master student will put especial emphasis in the theoretical grounds behind in order to design a variational framework combining the theoretical advantages of the considered techniques. In particular an optical flow based on Gabor phase tracking (developed in the group for medical imaging) will be generalized to urban scenes.  
  Address  
  Corporate Author Thesis Master's thesis  
  Publisher Place of Publication Bellaterra 08193, Barcelona, Spain Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ Mar2010 Serial 1582  
Permanent link to this record
 

 
Author Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil edit   pdf
doi  isbn
openurl 
  Title (up) Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging Type Book Chapter
  Year 2015 Publication Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal  
  Volume 9534 Issue Pages 69-79  
  Keywords  
  Abstract Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm.  
  Address Munich; Germany; January 2015  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-28711-9 Medium  
  Area Expedition Conference STACOM  
  Notes ADAS; IAM; 600.075; 600.076; 600.060; 601.145 Approved no  
  Call Number Admin @ si @ KHM2015 Serial 2734  
Permanent link to this record
 

 
Author Jaume Garcia; David Rotger; Francesc Carreras; R.Leta; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title (up) Contrast echography segmentation and tracking by trained deformable models Type Conference Article
  Year 2003 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 30 Issue Pages 173-176  
  Keywords  
  Abstract The objective of this work is to segment the human left ventricle myocardium (LVM) in contrast echocardiography imaging and thus track it along a cardiac cycle in order to extract quantitative data about heart function. Ultrasound images are hard to work with due to their speckle appearance. To overcome this we report the combination of active contour models (ACM) or snakes and active shape models (ASM). The ability of ACM in giving closed and smooth curves in addition to the power of the ASM in producing shapes similar to the ones learned, evoke to a robust algorithm. Meanwhile the snake is attracted towards image main features, ASM acts as a correction factor. The algorithm was tested independently on 180 frames and satisfying results were obtained: in 95% the maximum difference between automatic and experts segmentation was less than 12 pixels.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Centre de Visió per Computador – Dept. Informàtica, UAB Edifici O – Campus UAB, 08193 Bellater Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0276-6547 ISBN 0-7803-8170-X Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GRC2003 Serial 1512  
Permanent link to this record
 

 
Author Elena Valderrama; Joan Oliver; Josep Maria-Basart; Enric Marti; Petia Radeva; Ricardo Toledo; R.Vilanova;F.Ced; J.Muñoz; S.Vacchina edit  openurl
  Title (up) Convergencia al EEES de la ingeniería informática. Título de Grado en tecnología (Informática) Type Miscellaneous
  Year 2005 Publication I Jornades de Innovació Docent Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Elena Valderrama  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;RV;MILAB;ADAS Approved no  
  Call Number IAM @ iam @ VOB2005 Serial 1652  
Permanent link to this record
 

 
Author Joel Barajas; Jaume Garcia; Karla Lizbeth Caballero; Francesc Carreras; Sandra Pujades; Petia Radeva edit   pdf
isbn  openurl
  Title (up) Correction of Misalignment Artifacts Among 2-D Cardiac MR Images in 3-D Space Type Conference Article
  Year 2006 Publication 1st International Wokshop on Computer Vision for Intravascular and Intracardiac Imaging (CVII’06) Abbreviated Journal  
  Volume 3217 Issue Pages 114-121  
  Keywords  
  Abstract Cardiac Magnetic Resonance images offer the opportunity to study the heart in detail. One of the main issues in its modelling is to create an accurate 3-D reconstruction of the left ventricle from 2-D views. A first step to achieve this goal is the correct registration among the different image planes due to patient movements. In this article, we present an accurate method to correct displacement artifacts using the Normalized Mutual Information. Here, the image views are treated as planes in order to diminish the approximation error caused by the association of a certain thickness, and moved simultaneously to avoid any kind of bias in the alignment process. This method has been validated using real and syntectic plane displacements, yielding promising results.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Copenhagen (Denmark) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-540-22977-3 Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ BGC2006 Serial 1485  
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva edit  openurl
  Title (up) Curvature based Distance Maps Type Report
  Year 2003 Publication CVC Technical Report Abbreviated Journal  
  Volume Issue 70 Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Computer Vision Center Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GIR2003a Serial 1534  
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva edit   pdf
url  doi
isbn  openurl
  Title (up) Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling Type Book Chapter
  Year 2003 Publication Energy Minimization Methods In Computer Vision And Pattern Recognition Abbreviated Journal LNCS  
  Volume 2683 Issue Pages 357-372  
  Keywords Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature  
  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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer, Berlin Place of Publication Lisbon, PORTUGAL Editor Springer, B.  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 3-540-40498-8 Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GIR2003b Serial 1535  
Permanent link to this record
 

 
Author Debora Gil; Aura Hernandez-Sabate; David Castells; Jordi Carrabina edit   pdf
openurl 
  Title (up) CYBERH: Cyber-Physical Systems in Health for Personalized Assistance Type Conference Article
  Year 2017 Publication International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Assistance systems for e-Health applications have some specific requirements that demand of new methods for data gathering, analysis and modeling able to deal with SmallData:
1) systems should dynamically collect data from, both, the environment and the user to issue personalized recommendations; 2) data analysis should be able to tackle a limited number of samples prone to include non-informative data and possibly evolving in time due to changes in patient condition; 3) algorithms should run in real time with possibly limited computational resources and fluctuant internet access.
Electronic medical devices (and CyberPhysical devices in general) can enhance the process of data gathering and analysis in several ways: (i) acquiring simultaneously multiple sensors data instead of single magnitudes (ii) filtering data; (iii) providing real-time implementations condition by isolating tasks in individual processors of multiprocessors Systems-on-chip (MPSoC) platforms and (iv) combining information through sensor fusion
techniques.
Our approach focus on both aspects of the complementary role of CyberPhysical devices and analysis of SmallData in the process of personalized models building for e-Health applications. In particular, we will address the design of Cyber-Physical Systems in Health for Personalized Assistance (CyberHealth) in two specific application cases: 1) A Smart Assisted Driving System (SADs) for dynamical assessment of the driving capabilities of Mild Cognitive Impaired (MCI) people; 2) An Intelligent Operating Room (iOR) for improving the yield of bronchoscopic interventions for in-vivo lung cancer diagnosis.
 
  Address Timisoara; Rumania; September 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference SYNASC  
  Notes IAM; 600.085; 600.096; 600.075; 600.145 Approved no  
  Call Number Admin @ si @ GHC2017 Serial 3045  
Permanent link to this record
Select All    Deselect All
 |   | 
Details

Save Citations:
Export Records: