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Author Jorge Bernal; Joan M. Nuñez; F. Javier Sanchez; Fernando Vilariño
Title (down) Polyp Segmentation Method in Colonoscopy Videos by means of MSA-DOVA Energy Maps Calculation Type Conference Article
Year 2014 Publication 3rd MICCAI Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging Abbreviated Journal
Volume 8680 Issue Pages 41-49
Keywords Image segmentation; Polyps; Colonoscopy; Valley information; Energy maps
Abstract In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.
Address Boston; USA; September 2014
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 CLIP
Notes MV; 600.060; 600.044; 600.047;SIAI Approved no
Call Number Admin @ si @ BNS2014 Serial 2502
Permanent link to this record
 
 
Author Jorge Bernal
Title (down) Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps Type Book Whole
Year 2012 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Colorectal cancer is the fourth most common cause of cancer death worldwide and its survival rate depends on the stage in which it is detected on hence the necessity for an early colon screening. There are several screening techniques but colonoscopy is still nowadays the gold standard, although it has some drawbacks such as the miss rate. Our contribution, in the field of intelligent systems for colonoscopy, aims at providing a polyp localization and a polyp segmentation system based on a model of appearance for polyps. To develop both methods we define a model of appearance for polyps, which describes a polyp as enclosed by intensity valleys. The novelty of our contribution resides on the fact that we include in our model aspects of the image formation and we also consider the presence of other elements from the endoluminal scene such as specular highlights and blood vessels, which have an impact on the performance of our methods. In order to develop our polyp localization method we accumulate valley information in order to generate energy maps, which are also used to guide the polyp segmentation. Our methods achieve promising results in polyp localization and segmentation. As we want to explore the usability of our methods we present a comparative analysis between physicians fixations obtained via an eye tracking device and our polyp localization method. The results show that our method is indistinguishable to novice physicians although it is far from expert physicians.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor F. Javier Sanchez;Fernando Vilariño
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area 800 Expedition Conference
Notes MV Approved no
Call Number Admin @ si @ Ber2012 Serial 2211
Permanent link to this record
 
 
Author Jorge Bernal
Title (down) Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps Type Journal Article
Year 2014 Publication Electronic Letters on Computer Vision and Image Analysis Abbreviated Journal ELCVIA
Volume 13 Issue 2 Pages 9-10
Keywords Colonoscopy; polyp localization; polyp segmentation; Eye-tracking
Abstract Colorectal cancer is the fourth most common cause of cancer death worldwide and its survival rate depends on the stage in which it is detected on hence the necessity for an early colon screening. There are several screening techniques but colonoscopy is still nowadays the gold standard, although it has some drawbacks such as the miss rate. Our contribution, in the field of intelligent systems for colonoscopy, aims at providing a polyp localization and a polyp segmentation system based on a model of appearance for polyps. To develop both methods we define a model of appearance for polyps, which describes a polyp as enclosed by intensity valleys. The novelty of our contribution resides on the fact that we include in our model aspects of the image formation and we also consider the presence of other elements from the endoluminal scene such as specular highlights and blood vessels, which have an impact on the performance of our methods. In order to develop our polyp localization method we accumulate valley information in order to generate energy maps, which are also used to guide the polyp segmentation. Our methods achieve promising results in polyp localization and segmentation. As we want to explore the usability of our methods we present a comparative analysis between physicians fixations obtained via an eye tracking device and our polyp localization method. The results show that our method is indistinguishable to novice physicians although it is far from expert physicians.
Address
Corporate Author Thesis
Publisher Place of Publication Editor Alicia Fornes; Volkmar Frinken
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 Approved no
Call Number Admin @ si @ Ber2014 Serial 2487
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Author Ana Garcia Rodriguez; Jorge Bernal; F. Javier Sanchez; Henry Cordova; Rodrigo Garces Duran; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach
Title (down) Polyp fingerprint: automatic recognition of colorectal polyps’ unique features Type Journal Article
Year 2020 Publication Surgical Endoscopy and other Interventional Techniques Abbreviated Journal SEND
Volume 34 Issue 4 Pages 1887-1889
Keywords
Abstract BACKGROUND:
Content-based image retrieval (CBIR) is an application of machine learning used to retrieve images by similarity on the basis of features. Our objective was to develop a CBIR system that could identify images containing the same polyp ('polyp fingerprint').

METHODS:
A machine learning technique called Bag of Words was used to describe each endoscopic image containing a polyp in a unique way. The system was tested with 243 white light images belonging to 99 different polyps (for each polyp there were at least two images representing it in two different temporal moments). Images were acquired in routine colonoscopies at Hospital Clínic using high-definition Olympus endoscopes. The method provided for each image the closest match within the dataset.

RESULTS:
The system matched another image of the same polyp in 221/243 cases (91%). No differences were observed in the number of correct matches according to Paris classification (protruded: 90.7% vs. non-protruded: 91.3%) and size (< 10 mm: 91.6% vs. > 10 mm: 90%).

CONCLUSIONS:
A CBIR system can match accurately two images containing the same polyp, which could be a helpful aid for polyp image recognition.

KEYWORDS:
Artificial intelligence; Colorectal polyps; Content-based image retrieval
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 MV; no menciona Approved no
Call Number Admin @ si @ Serial 3403
Permanent link to this record
 
 
Author Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez
Title (down) Polyp Detection Benchmark in Colonoscopy Videos using GTCreator: A Novel Fully Configurable Tool for Easy and Fast Annotation of Image Databases Type Conference Article
Year 2018 Publication 32nd International Congress and Exhibition on Computer Assisted Radiology & Surgery Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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 CARS
Notes ISE; MV; 600.119 Approved no
Call Number Admin @ si @ BHM2018 Serial 3089
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Author C. Molina; J.B. Subirana
Title (down) Polynomial-Time Algorithm for 2D object recognition. Type Miscellaneous
Year 1995 Publication VI National Simposium on Pattern Recognition and image Analysis Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Cordoba
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 Approved no
Call Number Admin @ si @ MoS1995b Serial 231
Permanent link to this record
 
 
Author X. Orriols; Lluis Barcelo; X. Binefa
Title (down) Polynomial Fiber Description of Motion for Video Mosaicing, Proceeding ICIP 2001. Type Miscellaneous
Year 2001 Publication IEEE International Conference on Image Processing, Grecia, 1:1030–1033. Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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 Approved no
Call Number Admin @ si @ OBB2001a Serial 143
Permanent link to this record
 
 
Author Josep Llados; Enric Marti
Title (down) Playing with error-tolerant subgraph isomorphism in line drawings Type Conference Article
Year 1997 Publication VII National Symposium on Pattern Recognition and image Analysis Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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 DAG;IAM; Approved no
Call Number IAM @ iam @ LlM1997 Serial 1570
Permanent link to this record
 
 
Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados
Title (down) Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Conference Article
Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Graph representation of graphical documents often suffers from noise viz. spurious nodes and spurios edges of graph and their discontinuity etc. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance.
But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical
graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.
Address Bethlehem; PA; USA; August 2013
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 GREC
Notes DAG; 600.045; 600.056; 600.061; 601.152 Approved no
Call Number Admin @ si @ BDJ2013 Serial 2360
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Author Alex Gomez-Villa; Bartlomiej Twardowski; Kai Wang; Joost van de Weijer
Title (down) Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning Type Conference Article
Year 2024 Publication Winter Conference on Applications of Computer Vision Abbreviated Journal
Volume Issue Pages 1690-1700
Keywords
Abstract Continuous unsupervised representation learning (CURL) research has greatly benefited from improvements in self-supervised learning (SSL) techniques. As a result, existing CURL methods using SSL can learn high-quality representations without any labels, but with a notable performance drop when learning on a many-tasks data stream. We hypothesize that this is caused by the regularization losses that are imposed to prevent forgetting, leading to a suboptimal plasticity-stability trade-off: they either do not adapt fully to the incoming data (low plasticity), or incur significant forgetting when allowed to fully adapt to a new SSL pretext-task (low stability). In this work, we propose to train an expert network that is relieved of the duty of keeping the previous knowledge and can focus on performing optimally on the new tasks (optimizing plasticity). In the second phase, we combine this new knowledge with the previous network in an adaptation-retrospection phase to avoid forgetting and initialize a new expert with the knowledge of the old network. We perform several experiments showing that our proposed approach outperforms other CURL exemplar-free methods in few- and many-task split settings. Furthermore, we show how to adapt our approach to semi-supervised continual learning (Semi-SCL) and show that we surpass the accuracy of other exemplar-free Semi-SCL methods and reach the results of some others that use exemplars.
Address Waikoloa; Hawai; USA; January 2024
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 WACV
Notes LAMP Approved no
Call Number Admin @ si @ GTW2024 Serial 3989
Permanent link to this record
 
 
Author Simone Balocco; Carlo Gatta; Xavier Carrillo; F. Mauri; Petia Radeva
Title (down) Plaque Type, Plaque Burden and Wall Shear Stress Relation in Coronary Arteries Assessed by X-ray Angiography and Intravascular Ultrasound: a Qualitative Study Type Conference Article
Year 2011 Publication 14th International Symposium on Applied Sciences in Biomedical and Communication Technologies Abbreviated Journal
Volume Issue Pages
Keywords
Abstract In this paper, we present a complete framework that automatically provides fluid-dynamic and plaque analysis from IVUS and Angiographic sequences. Such framework is used to analyze, in three coronary arteries, the relation between wall shear stress with type and amount of plaque. Preliminary qualitative results show an inverse relation between the wall shear stress and the plaque burden, which is confirmed by the fact that the plaque growth is higher on the wall having concave curvature. Regarding the plaque type it was observed that regions having low shear stress are predominantly fibro-lipidic while the heavy calcifications are in general located in areas of the vessel having high WSS.
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 978-1-4503-0913-4 Medium
Area Expedition Conference ISABEL
Notes MILAB Approved no
Call Number Admin @ si @ BGC2011b Serial 1799
Permanent link to this record
 
 
Author Simone Zini; Alex Gomez-Villa; Marco Buzzelli; Bartlomiej Twardowski; Andrew D. Bagdanov; Joost Van de Weijer
Title (down) Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training Type Conference Article
Year 2023 Publication 11th International Conference on Learning Representations Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Several recent works on self-supervised learning are trained by mapping different augmentations of the same image to the same feature representation. The data augmentations used are of crucial importance to the quality of learned feature representations. In this paper, we analyze how the color jitter traditionally used in data augmentation negatively impacts the quality of the color features in learned feature representations. To address this problem, we propose a more realistic, physics-based color data augmentation – which we call Planckian Jitter – that creates realistic variations in chromaticity and produces a model robust to illumination changes that can be commonly observed in real life, while maintaining the ability to discriminate image content based on color information. Experiments confirm that such a representation is complementary to the representations learned with the currently-used color jitter augmentation and that a simple concatenation leads to significant performance gains on a wide range of downstream datasets. In addition, we present a color sensitivity analysis that documents the impact of different training methods on model neurons and shows that the performance of the learned features is robust with respect to illuminant variations.
Address 1 -5 May 2023, Kigali, Ruanda
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 ICLR
Notes LAMP; 600.147; 611.008; 5300006 Approved no
Call Number Admin @ si @ ZGB2023 Serial 3820
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Author Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa
Title (down) Planar-Based Multispectral Stereo Type Conference Article
Year 2012 Publication 11th Quantitative InfraRed Thermography Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Naples, Italy
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 QIRT
Notes ADAS Approved no
Call Number Admin @ si @ BLA2012 Serial 2016
Permanent link to this record
 
 
Author Ishaan Gulrajani; Kundan Kumar; Faruk Ahmed; Adrien Ali Taiga; Francesco Visin; David Vazquez; Aaron Courville
Title (down) PixelVAE: A Latent Variable Model for Natural Images Type Conference Article
Year 2017 Publication 5th International Conference on Learning Representations Abbreviated Journal
Volume Issue Pages
Keywords Deep Learning; Unsupervised Learning
Abstract Natural image modeling is a landmark challenge of unsupervised learning. Variational Autoencoders (VAEs) learn a useful latent representation and generate samples that preserve global structure but tend to suffer from image blurriness. PixelCNNs model sharp contours and details very well, but lack an explicit latent representation and have difficulty modeling large-scale structure in a computationally efficient way. In this paper, we present PixelVAE, a VAE model with an autoregressive decoder based on PixelCNN. The resulting architecture achieves state-of-the-art log-likelihood on binarized MNIST. We extend PixelVAE to a hierarchy of multiple latent variables at different scales; this hierarchical model achieves competitive likelihood on 64x64 ImageNet and generates high-quality samples on LSUN bedrooms.
Address Toulon; France; April 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 ICLR
Notes ADAS; 600.085; 600.076; 601.281; 600.118 Approved no
Call Number ADAS @ adas @ GKA2017 Serial 2815
Permanent link to this record
 
 
Author Shida Beigpour
Title (down) Physics-based Reflectance Estimation Applied to Recoloring Type Report
Year 2009 Publication CVC Technical Report Abbreviated Journal
Volume 137 Issue Pages
Keywords
Abstract
Address
Corporate Author Computer Vision Center Thesis Master's thesis
Publisher Place of Publication Bellaterra, Barcelona 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 CIC Approved no
Call Number Admin @ si @ Bei2009 Serial 2396
Permanent link to this record